WEST INDIAN JOURNAL OF ENGINEERING Editorial……………………………………………………………………………….…………….……… 2 Density-Moisture Relations of Two Trinidad Soils Obtained with a Soil Vibratory Compactor …………. 4 A Low-Cost IoT Based Neonatal Incubator for Resource Poor Settings …………………...……………... 11 Testing of Physical-Mechanical Properties of Blue Limestone Used in Pavements in Trinidad and Tobago: A Preliminary Study …………….………………………………………………………………. 21 Adsorption of Pb(II) and Phenol from Wastewater Using Silver Nitrate Modified Activated Carbon from Groundnut (Arachis hypogaea L.) Shells …………………………………….…...……………….. 26 Differences between Technicians and Engineers: An Analysis Based on UK-SPEC ……………….……. 36 Contextual Analysis of Innovation Process Models toward the Fourth Industrial Revolution ……….…… 43 Published by: Faculty of Engineering, The University of the West Indies St Augustine, Trinidad and Tobago, West Indies Volume 43 • Number 1 (ISSN 0511 5728) • July 2020 .
Density-Moisture Relations of Two Trinidad Soils Obtained with a Soil Vibratory Compactor …………. 4
A Low-Cost IoT Based Neonatal Incubator for Resource Poor Settings …………………...……………... 11
Testing of Physical-Mechanical Properties of Blue Limestone Used in Pavements in Trinidad and Tobago: A Preliminary Study …………….………………………………………………………………. 21
Adsorption of Pb(II) and Phenol from Wastewater Using Silver Nitrate Modified Activated Carbon from Groundnut (Arachis hypogaea L.) Shells …………………………………….…...……………….. 26
Differences between Technicians and Engineers: An Analysis Based on UK-SPEC ……………….……. 36
Contextual Analysis of Innovation Process Models toward the Fourth Industrial Revolution ……….…… 43
Published by: Faculty of Engineering, The University of the West Indies
St Augustine, Trinidad and Tobago, West Indies
Volume 43 • Number 1 (ISSN 0511 5728) • July 2020 .
WEST INDIAN JOURNAL OF ENGINEERING
The WIJE Editorial Office Faculty of Engineering, The University of the West Indies, St Augustine
The Republic of Trinidad and Tobago, West Indies Tel: (868) 662-2002, ext. 83459; Fax: (868) 662-4414;
The West Indian Journal of Engineering, WIJE (ISSN 0511-5728) is an international journal which has a focus on the Caribbean region. Since its inception in September 1967, it is published twice yearly by the Faculty of Engineering at The University of the West Indies (UWI) and the Council of Caribbean Engineering Organisations (CCEO) in Trinidad and Tobago. WIJE aims at contributing to the development of viable engineering skills, techniques, management practices and strategies relating to improving the performance of enterprises, community, and the quality of life of human beings at large. Apart from its international focus and insights, WIJE also addresses itself specifically to the Caribbean dimension with regard to identifying and supporting the emerging research areas and promoting various engineering disciplines and their applications in the region.
The Publications and Editorial Board Professor Edwin I. Ekwue, Chairman (Dean, Faculty of Engineering), UWI; E-mail: [email protected]
Professor Boppana V. Chowdary, Vice-Chairman (Deputy Dean, R&PG Affairs), UWI; E-mail: [email protected]
Professor Stephan J.G. Gift, Member (Immediate Past Chairman), UWI; E-mail: [email protected]
Professor Kit Fai Pun, Member (Editor), UWI; E-mail: [email protected]
Professor Winston A. Mellowes, Member (Immediate Past Editor), UWI; E-mail: [email protected]
Dr. Jacqueline Bridge, Member (Mechanical & Manufacturing Engineering), UWI; [email protected]
Dr. Michael Sutherland, Member (Geomatics Engineering and Land Management), UWI; E-mail: [email protected] Dr. Fasil Muddeen, Member (Electrical & Computer Engineering), UWI; E-mail: [email protected]
Dr. Raffie Hosein, Member (Chemical Engineering), UWI; E-mail: [email protected] Dr. Trevor A. Townsend, Member (Civil & Environmental Engineering), UWI; E-mail: [email protected]
International Editorial Advisory Committee Professor Andrew K.S. Jardine, University of Toronto, Toronto, Canada; E-mail: [email protected]
Professor Andrew Wojtanowicz, Louisiana State University, Louisiana, USA; E-mail: [email protected]
Professor Clive E. Davies, Massey University, Palmerston North, New Zealand; E-mail: [email protected]
Professor John Yilin Wang, The Pennsylvania State University, Pennsylvania PA, USA; E-mail: [email protected] Professor Joseph K. Ssegawa, University of Botswana, Gaborone, Africa; E-mail: [email protected] Professor Marehalli G. Prasad, Stevens Institute of Technology, Hoboken, New Jersey, USA, E-mail: [email protected] Professor Nageswara Rao Posinasetti, University of Northern Iowa, Cedar Falls IA, USA, E-mail: [email protected] Professor Prasanta Kumar Dey, Aston University, Birmingham, UK; E-mail: [email protected]
Professor Richard Hobbs, University of Durham, Nuffield, Durham, U.K.; E-mail: [email protected]
Professor V.M. Rao Tummala, Eastern Michigan University, Ypsilanti MI, USA; E-mail: [email protected] Professor Wach Grant, Dalhousie University, Halifax, Nova Scotia, Canada; E-mail: [email protected]
Dr. Albert H.C. Tsang, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China; E-mail: [email protected] Dr. Henry Lau, University of Western Sydney, Parramatta Campus, Sydney, Australia; E-mail: [email protected]
Dr. Jeffery A. Jones, University of Warwick, Coventry, UK; E-mail: [email protected] Dr. Kiran Tota-Maharaj, University of the West of England (UWE), Bristol, U.K.; E-mail: [email protected]
Dr. Kwai-Sang Chin, City University of Hong Kong, Kowloon, Hong Kong, China; E-mail: [email protected]
Dr. Morris Abraham G. Ezra, Universiti Tunku Abdul Rahman, Kajang, Selangor Malaysia; E-mail: [email protected]
Editorial Sub-Committee Professor Kit Fai Pun, Chairman and Editor (Office of Industrial Engineering), UWI; E-mail: [email protected]
Dr. Chris Maharaj, Vice Chair (Mechanical & Manufacturing Engineering), UWI; E-mail: [email protected]
Mr. Kevon Andrews, Member (Electrical & Computer Engineering), UWI; E-mail: [email protected] Ms. Crista Mohammed, Member (Electrical & Computer Engineering), UWI; E-mail: [email protected]
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To order subscriptions or report change of address, simply fill in the required information on the Subscription Order Form provided at the back of the Journal or downloaded from the WIJE website, and/or write to: The Editor-in-Chief, The Editorial Office, West Indian Journal of Engineering, c/o Block #1, Faculty of Engineering, The University of the West Indies, St Augustine, Trinidad and Tobago, West Indies. Fax: (868) 662 4414; Emails: [email protected]; [email protected]
WIJE; Vol. 43, No1, July 2020
1
WEST INDIAN JOURNAL
OF ENGINEERING
2 Editorial
4 Density-Moisture Relations of Two Trinidad Soils Obtained with a
Soil Vibratory Compactor by Edwin I. Ekwue, Aliyah Abasali, Carlotta Bharat and Robert A. Birch
11 A Low-Cost IoT Based Neonatal Incubator for Resource Poor
Settings by Solomon C. Nwaneri, Jesubori W. Sojobi, Aderounwi O. Oyelade,
Beatrice N. Ezenwa, Oluwaseyi J. Balogun, and Ugochi C. Uregbulam
21 Testing of Physical-Mechanical Properties of Blue Limestone Used
in Pavements in Trinidad and Tobago: A Preliminary Study by Kailas S. Banerjee, and Shane Kassie
26 Adsorption of Pb(II) and Phenol from Wastewater Using Silver
Nitrate Modified Activated Carbon from Groundnut (Arachis
hypogaea L.) Shells by Omodele A. A. Eletta, Ibrahim O. Tijani, and Joshua O. Ighalo
36 Differences between Technicians and Engineers: An Analysis Based
on UK-SPEC by Terrence R.M. Lalla and Nadine Sangster
43 Contextual Analysis of Innovation Process Models toward the
Fourth Industrial Revolution by Ambika Koonj Beharry and Kit Fai Pun
Volume 43 • Number 1
(ISSN 0511-5728) • July 2020
The Editorial Office West Indian Journal of Engineering
Faculty of Engineering The University of the West Indies
The West Indian Journal of Engineering (WIJE) is an international journal which publishes research in the engineering sciences, with relevance to the Caribbean. First published in 1967, WIJE is now its 43rd volume (No.1) as at July 2020.
WIJE Online is a static repository of approximately 800 peer-reviewed articles. Meanwhile, the website has limited functionality. With the support from the UWI - Campus Research and Publication Fund, WIJE had initiated a web project on “expanding the online interface of The West Indian Journal of Engineering to foster engineering research and publication in the Caribbean”. The project had commenced in 2018. The Journal Editorial Sub-Committee has been working over the past years on this project, and has been moving to the pilot testing phase.
The COVID-19 global health crisis is a unique challenge that has impacted many people, activities and projects, including the pilot testing of the WIJE-web project. The work schedule for testing had been postponed. It is expected that the testing be resumed in the coming months and be completed in line with the publishing of next January 2021 and July 2021 issues of the journal (i.e., Vol.43, No.2 and Vol.44, No.1). For facilitating the pilot test, it is planned to have a dual system with both the current operations and new pilot mode running in parallel for the coming issues.
II. About this Issue
For this Volume 43 Number 1, a total of 25 research/ technical articles were received. Of them, six (6) manuscripts have been accepted, whereas ten (10) are still under peer review and nine (9) papers were rejected and/or not considered. The relevance and usefulness of the 6 accepted articles are summarised below.
E.I. Ekwue et al., “Density-Moisture Relations of Two Trinidad Soils Obtained with a Soil Vibratory Compactor”, described the design of a mechanism and constructed of a soil vibratory compaction machine that vibrated the soil at a given time, amplitude and frequency and resulted in compacting the soil. The authors utilised a vibratory compactor working at the pre-determined parameters to test the density-moisture relations of two soils (sandy loam and clay) treated with peat at five different contents by mass and compacted at moisture contents which ranged from 5% to 55%. Similar tests were carried out using the standard Proctor test so as to compare the results. Results generally showed that although most bulk density values determined using the soil vibratory compactor were slightly lower than the values from the standard Proctor test, density values from the two methods were perfectly related. It was claimed
that the soil vibratory compactor could be used to estimate the bulk density values that are obtainable using the Proctor test. It could reduce the tedium involved in the standard Proctor soil compaction test.
In the article, “A Low-cost IoT Based Neonatal Incubator for Resource Poor Settings”, S.C. Nwaneri et
al., explored the use of an Internet of Things (IoT) based neonatal incubator with phototherapy blanket to mitigate the problem of high infant mortality in resource poor countries. The incubator was constructed, and an IoT platform was developed for real-time monitoring of temperature and humidity of the incubator. Modelling and simulation of the incubator environment based on standard thermodynamic principles were performed using Python programming language. It was claimed that a relatively stable temperature and humidity suitable for an infant was observed in the developed device. The IoT platform was effective in monitoring the temperature and humidity of the device. The environmental conditions were found to be suitable for a neonate. The device was effective for real-time monitoring of environmental conditions in the incubator.
K.S. Banerjee, and S. Kassie, “Testing of Physical-Mechanical Properties of Blue Limestone Used in Pavements in Trinidad and Tobago: A Preliminary Study”, investigated the toughness and abrasion resistance of the aggregate prior to its usage in Trinidad and Tobago. It was found that aggregate crushing and aggregate impact values were nearly two times lower in the massive limestone than the layered limestone. The loads required for the 10% fines were more than two times lower in the layered limestone than the massive quality. The specific gravity values were different in layered and massive limestones (2.3 and 2.5 respectively). Moreover, these measured mechanical properties were combined into a single characteristic, Toughness Index (TI), as performance indicator of overall quality of aggregates. The TI values also suggested that the layered limestones were weaker than the massive limestone. The layered limestones did not satisfy the needs to be aggregates of international quality for pavement construction. The massive limestones were found suitable for this purpose.
O.A.A. Eletta, I.O. Tijani, and J.O. Ighalo, “Adsorption of Pb(II) and Phenol from Wastewater Using Silver Nitrate Modified Activated Carbon from Groundnut (Arachis hypogaea L.) Shells”, presented the findings of a study that was to remove Pb(II) and phenol from pharmaceutical wastewater using activated carbon derived from Silver nitrate modified groundnut shells. The adsorbents were characterised by Fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM) and X-ray Diffraction (XRD) analysis. It was found that the adsorption of both Pb(II) and phenol was best fit to Langmuir isotherm and pseudo-second order kinetic models. The monolayer adsorption capacity
WIJE; Vol. 43, No.1, July 2020
3
of the modified adsorbent for Pb(II) and phenol were 123.2 mg/g and 115.5 mg/g, respectively. The adsorption process for both Pb(II) and phenol was exothermic and spontaneous.
In the fifth article, “Differences between Technicians and Engineers: An Analysis Based on UK-SPEC”, T.R.M. Lalla and N. Sangster, examined the competencies and commitment requirements of five (5) generic areas for Engineering Technicians (EngTech), Incorporated Engineers (IEng) or Technologists, and Chartered Engineers (CEng), as specified by the United Kingdom Standard for Professional Engineering Competence (UK-SPEC). These areas are: Knowledge and Understanding (KU); Design and Development of processes, systems, services and products (DD); Responsibility, Management or Leadership (RML); Communication and Inter-personal Skills (CIPS), and Professional Commitment (PC). The similarities and differences have been articulated in keywords associated by specific roles and responsibilities of EngTech, IEng and CEng. The study analysed the job advertisements for recruitment of technicians and engineers in Trinidad and Tobago, with respect to the UK SPEC. The findings suggested that firm’s Top Management to clarify the blurred lines of roles, responsibilities and authorities amongst EngTech, IEng and CEng. Respective skills set of technicians versus engineers could be pooled to improve team effectiveness in their workplace. An Engineering Competency Structure (ECS) was proposed which could be of immense value to engineering professionals in fostering better teamwork between the two, hence increasing their effectiveness and efficiencies.
A. Koonj Beharry and K.F. Pun, “Contextual Analysis of Innovation Process Models toward the Fourth Industrial Revolution”, explored the innovation-industrialisation relationship, and related the evolution of innovation concepts to various phases of industrial revolutions. In this paper, advocates and features of nine (9) innovation process models in the innovation literature were analysed, and a comparative analysis of innovation processes was made. It compared the different stages of the innovation process as advocated in respective models, and identified their main contextual themes – 1) strategy; 2) management; 3) organisational culture; 4) organisational learning and 5) communication. Several endogenous factors were identified, and the most common ones, were customer-centric focus, market orientation and future-orientation (from the strategy domain), support for innovation (from the management domain), and inter-firm communication (from the communication domain). The paper contributed to the identification of the contextual themes and factors of innovation process models with organisational learning at the firm’s level.
On behalf of the Editorial Office, we gratefully acknowledge all authors who have made this special issue possible with their research work. We greatly appreciate
the voluntary contributions and unfailing support that our reviewers give to the Journal.
Our reviewer panel is composed of academia, scientists, and practising engineers and professionals from industry and other organisations as listed below:
• Dr. Albert H.C. Tsang, Hong Kong Polytechnic University, Hong Kong (HK)
• Professor Andrew K.S. Jardine; University of Toronto, Toronto, Canada
• Professor Andrew Ordys; University of Warsaw, Warszawa, Poland
• Professor C. Elvis López Bravo; Central University “Marta Abreu” of Las Villas, Villa Clara, Cuba
• Dr. Chris Maharaj; The University of the West Indies (UWI), St Augustine, Trinidad and Tobago (T&T)
• Ms. Crista Mohammed, UWI, St Augustine, T&T
• Dr. Daniel White; The University of Trinidad and Tobago (UTT), T&T
• Professor Eugene D. Coyle; Military Technological College (MTC), Muscat - Sultanate of Oman
• Dr. Graham King; UWI, St Augustine, T&T
• Dr. Igor Jokanovic; University of Novi Sad, Subotica, Republic of Serbia
• Dr. Jeffrey Smith; UWI, St Augustine, T&T
• Dr. John Joseph; Utilities Engineering Group, UTT, T&T
• Mr. Kishore Jhagroo; UWI, St Augustine, T&T
• Professor Kit Fai Pun; UWI, St Augustine, T&T
• Professor M. Srinivas Kini; Manipal Institute of Technology, Karnataka State, India
• Ms. Man Yin Rebecca Yiu, UWI, St. Augustine T&T
• Dr. Mark Wuddivira; UWI, St Augustine, T&T
• Professor Oladipupo Ogunleye; Ladoke Akintola University of Technology, Nigeria
• Professor Olusegun Kehinde Abiola; Federal University of Petroleum Resources Effurun, Nigeria
• Professor Onkar Singh Bhatia; Green Hills Engineering College Solan, India.
• Dr. Rean Maharaj; UTT, T&T
• Professor Reynold Stone; UWI, St Augustine, T&T
• Dr. Sunil Rohan Tittagala; Sheffield Hallam University, Sheffield, UK
• Dr. Thomas F. Garrison; King Fahd University of Petroleum & Minerals, Dhahran, Saudi Arabia
• Dr. Umesh Persad; UTT, T&T
The views expressed in articles are those of the authors to whom they are credited. This does not necessarily reflect the opinions or policy of the Journal.
KIT FAI PUN, Editor-in-Chief
Faculty of Engineering, The University of the West Indies,
St Augustine, Trinidad and Tobago, West Indies
July 2020
E.I. Ekwue et al.: Density-Moisture Relations of Two Trinidad Soils Obtained with a Soil Vibratory Compactor 4
Density-Moisture Relations of Two Trinidad Soils Obtained with a Soil
Vibratory Compactor
Edwin I. Ekwue a,Ψ; Aliyah Abasalib, Carlotta Bharatc and Robert A. Birchd
Department of Mechanical and Manufacturing Engineering, The University of the West Indies, St. Augustine, Trinidad and Tobago, West Indies;
(Received 17 May 2019; Revised 09 February 2020; Accepted 08 April 2020)
Abstract: Density-moisture relations are required while constructing roads and other structures and during farming
operations. The Proctor test is the standard method of determining this relationship but other methods exist including
the vibratory hammer or table and the soil vibratory compactor. The design, construction and testing of a soil
vibratory compaction machine, which could produce maximum densities that mimic the Proctor test has been
described in a previous paper by Leonard et al. (2019). A mechanism was designed and developed that vibrated the
soil at a given time, amplitude and frequency and resulted in compacting the soil. It was determined that 17 Hz
frequency operating at an amplitude of 1.7 mm for 5 mins were the ideal parameters to operate the compactor.
However, it is still unclear whether the soil vibratory compactor could be used to test soils with varying clay contents
with different water and organic matter contents. This paper utilises a vibratory compactor working at the pre-
determined parameters to test the density-moisture relations of two soils (sandy loam and clay) treated with peat at
five different contents (0%, 4%, 8%, 12% and 16%) by mass and compacted at moisture contents which ranged from
5% to 55%. Similar tests were carried out using the standard Proctor test so as to compare the results. Results
generally showed that although most bulk density values determined using the soil vibratory compactor were slightly
lower (within a range of 0.02 to 0.06 t m-3) than the values from the standard Proctor test, density values from the two
methods were perfectly related (r = 0.998). The soil vibratory compactor could then be used to estimate the bulk
density values that are obtainable using the Proctor test. The major advantage of the constructed soil vibratory
compaction equipment is that it could reduce the tedium involved in the standard Proctor soil compaction test.
Keywords: Soil, compaction, vibration, Proctor, test
1. Introduction
Before structures like buildings, dams, airports or roads are built there is the need to do a compaction test of the soils in the area so as to determine the optimum moisture content for maximum compaction. During compaction, water which acts as a lubricant and allows the soil particles to be aligned and packed properly is added to the soil (Felton and Ali, 1992; Ekwue et. al., 2005). Too much water, however, reduces the density of the soil (Ohu et al., 1985). Thus for a given compaction effort, using compacting forces like ramming, vibration and static rollers, there is an optimum water content at which maximum soil density is achieved. On the other hand, soil compaction is undesirable in agricultural practice since it reduces soil aeration, water availability to plants and imparts high mechanical impedance to root growth (Thompson et al., 1987). There is, therefore, the need for the engineer to know this maximum density as well as the optimum water content for maximum soil compaction, and these are normally obtained by prior
laboratory tests. The agriculturist needs the information since it is desirable to limit soil working below the optimum water content, so as to reduce compaction on the soil.
In the literature, the standard Proctor and the modified Proctor tests are the standard methods for determining maximum density and the optimum water content for maximum compaction. The Proctor tests are the most common and involve dropping a 2.5-kg hammer (4.5 kg for the modified test) from a height of 305 mm (450 mm for the modified) onto a sieved soil at a particular water content contained in a cylindrical mould, 0.001 m3 volume (0.002 m3 for the modified) in three (five for the modified) layers. This is dropped 25 times (27 for the modified) for each soil layer (ASTM, 2007). The test is continued for increasing water contents until maximum soil density is obtained, and the water content at which this occurs is called the optimum water content for the soil (Ekwue and Stone, 1994). The standard Proctor and modified Proctor tests are very
ISSN 0511-5728 The West Indian Journal of Engineering
Vol.43, No.1, July 2020, pp.4-10
E.I. Ekwue et al.: Density-Moisture Relations of Two Trinidad Soils Obtained with a Soil Vibratory Compactor
5
laborious due to the manual nature of the standard procedure and this has prompted researchers to examine other methods. The vibratory hammer and the vibrating table tests have been devised. The vibration hammer test involves compaction of the soil in a mould similar to the Proctor test using an electrically operated vibrating hammer. The hammer is allowed to vibrate on each of the three layers for about 60 seconds (British Standards Institution, 1990). The vibrating table test, which is the American Standard (ASTM, 2006), is similar to the vibratory hammer test except that the soil in the mould is placed on a table that vibrates and the level of compaction achieved depends on the frequency and amplitude of vibration, as well as the size and shape of the mould in which it is vibrating (Dobry and Whitman, 1973). The density obtained for the soils using the vibrating soil test equipment (such as the vibrating hammer) is comparable to that from the modified Proctor test but is generally greater than that from the standard Proctor test (Prochaska and Drevich, 2005; Waldemar and Lechocka, 2016)
In a previous paper, Leonard et al. (2019) described a soil vibratory compactor which could be utilised to carry out similar tests. These authors examined the various operating parameters of the vibratory compactor and determined that at a frequency of 17 Hz, with an amplitude of 1.17 mm for 5 mins, the maximum densities measured using the vibratory soil compactor were very close to those obtained using the standard Proctor test. It was found that this applied to all soils particularly the sandy soils with low cohesion. Organic matter in form of peat in the presence of water was found to decrease cohesion in sandy soils but to increase it in clay soils (Ekwue et al., 2014). It is not therefore very clear from the previous study whether the soil vibratory compactor could also be used to test soils with a wide variety of properties including different water and organic matter contents. This study tested two soils with five peat contents and utilised the vibratory soil compaction at the ideal operating conditions prescribed by Leonard et al. (2019) and compared the results obtained with those obtained using the standard Proctor test. The aim was to test soils with high organic matter contents and variable water contents using the Proctor and vibratory compactor tests to determine the extent to which the results from both tests were comparable. 2. Description of the Constructed Soil Vibratory
Compactor
2.1 Construction and Operation
This soil vibratory compactor (see Figure 1) was fully described by Leonard et al. (2019). The only alteration to this compactor was the replacement of the soil mould with a standard Proctor mould which is split in two pieces and the base of the mould was made separate so as to allow the soil to be easily removed after each test.
The compactor operates on the principle of rotating unbalanced induced vibrations. A shaft is connected to the frame via bearings which are supported by the internal frame. During operation of the soil vibratory compactor, a soil sample is placed in the bottom mould (the same size of the standard Proctor mould) for the first layer of compaction. The motor is then energised. The speed of the motor is set using a variable speed drive and this alters the frequency (determined using accelerometers) of the vibration of the soil compactor. The soil sample in the mould is allowed to vibrate for a given period of time at specific frequencies and amplitudes. Once the first soil layer has been compacted, the procedure is repeated for two other soil layers of equal volume.
Figure 1. The soil vibratory compactor
3. Testing of the Soils Using the Constructed Vibratory Soil Compactor and the Standard
Proctor Equipment
3.1 Purpose of the Tests
The purpose of the tests was to utilise the optimum operating parameters (frequency of 17 Hz, amplitude of 1.7 mm and time of 5 mins) for the vibratory soil compactor and obtain the density of two soils, each with five varying peat contents. The same soils were also tested using the standard Proctor test.
3.2 Procedure of the Testing
For both the standard Proctor test and the test using the constructed soil vibratory compactor, two soil samples common in Trinidad (see Table 1) were utilised: Piarco sandy loam, and Talparo clay. Soil texture was determined by the hydrometer method (ASTM, 2017), while the organic matter contents were determined using the Walkley and Black (1943) method. The soils were first dried, and sieved through 5 mm openings.
E.I. Ekwue et al.: Density-Moisture Relations of Two Trinidad Soils Obtained with a Soil Vibratory Compactor
6
Table 1. Classification, organic matter, and the particle size distribution (%) of the soils
* Classification according to the Soil Taxonomy System (Source: Ditzler, 2017) ** All values are means of three replicates
Peat was then incorporated at five levels of 0%, 4%,
8%, 12%, and 16%. For the Proctor compaction test, soil was compacted in three even layers at 25 blows each for increasing moisture contents ranging from 5% to 55%. Once the soil had been compacted, the extension of the mould was removed, the excess soil was scraped off and the mould was weighed. The mass of the compacted soil was measured and was then used to determine the dry bulk density.
For the vibratory soil compactor, the initial weight of the empty mould was first obtained. Soils at the same peat and water contents as in the Proctor test were poured into the mould in three equal layers to be compacted for the 5 mins duration each. After the soil had been compacted, the extension was removed, excess soil scraped off and the mould was weighed. This was done to determine the bulk density of the soil and this was compared to that obtained with the standard Proctor test. In both cases, graphs of dry bulk density vs. moisture content were plotted following the examples in previous research (de Kimpe et al., 1982; Felton and Ali, 1992; Ekwue and Stone, 1995; Leonard et al., 2019).
4. Results and Discussion
4.1 Operation of the Soil Vibratory Compactor
During the testing, it was observed that the constructed soil vibratory compactor produced sinusoidal vibration. There was noise generated from the shaking parts though it was bolted to the table and rubber pads were used. The legs of the table that the vibratory compactor rested on were cut and the table was fortified by bracing. Determining maximum dry bulk density using the vibratory soil compactor was not as laborious in nature when compared to the standard Proctor test. However, some effort was required to prepare the samples and remove the mould after each compaction. 4.2 Proctor Test and Soil Vibratory Compactor Test
Results
Figure 2 shows the plots of the bulk density-moisture relations of the two soils, each with five varying peat contents using the 25 blows of the standard Proctor method compared with the same plots obtained using the soil vibratory compactor. As expected, for the two soils and methods, the results followed the normal soil behaviour, whereby the density values increased up to maximum values, called the maximum bulk density after which they decreased with further increases in moisture
content. This is typical soil behaviour. The density values obtained for these soils and the moisture contents at which they occurred were similar to those obtained for the same soils using the Proctor test in previous studies by Stone and Ekwue (1993), Ekwue and Stone (1994), Ekwue and Stone (1995) and Leonard et al. (2019).
Figure 2. Density-water relations of the Piarco sandy loam and Talparo clay soils using the standard Proctor test and the soil
vibratory compactor
Also as expected, the bulk density values for Piarco
sandy soil were generally greater than those for the Talparo soil. Sandy soils are more compactable than clay soils (Ekwue and Stone, 1995; Suryakanta, 2014). This is because they contain less air voids and have little cohesion between the soil particles. In each case, as expected, the bulk density values decreased with increasing peat contents as peat is known to be less dense and therefore reduces soil bulk density (Ohu et al., 1985; Ekwue and Stone, 1994).
Most values of the bulk densities obtained with the soil vibratory compactor were lower than the Proctor ones by 0.02 to 0.06 t m-3 with a mean difference of 0.03 t m-3 (see Figure 2). The 95% confidence interval for the mean differences is (-0.04, -0.03). Since this confidence interval does not include zero, the difference between the means were significant at 5% level. This was confirmed by using a paired t-test which showed a significant (P = 0.05) t-value of – 14.83 between the two means.
E.I. Ekwue et al.: Density-Moisture Relations of Two Trinidad Soils Obtained with a Soil Vibratory Compactor
7
Table 2. Maximum bulk densities using the soil vibratory compactor and the standard Proctor test
*Proportion of the value from the standard Proctor test
In general, maximum bulk densities obtained using
the soil vibratory compactor were within 96% to 98% of corresponding values obtained using the Proctor test (see Table 2) and were lower by 0.02 to 0.06 with a mean of difference of -0.04 t m-3. The 95% confidence interval is -0.05, -0.03. Since this interval does not contain zero, this also means that the differences between the mean values were significantly different at 5% level. This again was confirmed by a paired t-test value of -12.86, which is significant at 5%. The mean differences between the two soil compaction methods in both cases were well less than 0.1 t m-3 and are well within the error expected in soil measurements, bearing in mind that soils by their nature are very variable and complex. This is similar to the results obtained by Leonard et al. (2019).
As showed in Figure 3, the values for the bulk densities obtained using the two methods are highly correlated, although the 1:1 line drawn through the points demonstrated that most of the soil vibratory compactor values were slightly lower than the standard Proctor ones as already mentioned.
Figure 3. Comparison of bulk density using the two soil compaction methods
As explained in the materials and methods section,
the soils were incorporated with the same levels of peat and compared at the same water contents. Results show that the values obtained with the soil vibratory compactor are lower but very close to the ones that obtained using the standard Proctor test. The new compactor is gives mostly reliable results. The present study has demonstrated in particular that the optimum
operating parameters for the soil vibratory compactor developed in the previous study by Leonard et al. (2019) applies equally to the soils with different levels of organic matter content. This finding was not evident before the present study since organic matter in form of peat affects the soil cohesion, which influences the efficiency of the operation of the soil vibratory compactor.
4.3 Factors Affecting the Values of Bulk Densities in
the Proctor Test and the Soil Vibratory Compactor
Table 3 summarises the mean values of dry bulk densities for the different experimental factors. The two soils with the peat contents were compared at the common four moisture contents of 15%, 20%, 25% and 30%. The mean values followed the same trend in Figures 2 and 3. It shows that there is little or no difference between the bulk densities (1.34 and 1.31 t m-
3) obtained with the two compaction methods. The mean value of bulk density was greater for Piarco sandy soil (1.57 t m-3) than the Talparo clay (1.07 t m-3). This is not surprising since it is known that sandy soils which are less cohesive have higher bulk density than the clay soils which are more cohesive and more aggregated (Ekwue et al., 2014; Suryakanta, 2014).
Table 3. Mean* bulk densities for the experimental factors
Factor Dry bulk density (t m-3)
Method of compaction Standard Proctor test Soil vibratory compactor
1.34 1.31
Soil type: Piarco sandy loam Talparo clay
1.57 1.07
Peat content (%): 0 4 8 12 16
1.51 1.43 1.34 1.24 1.09
Moisture content (%): 15 20 25 30
1.25 1.31 1.36 1.38
* - Mean values for each factor were computed by averaging values over the levels of the other three experimental factors. Number of experimental points is 160 representing a factorial experiment with 2 methods of soil compaction, 2 soil types, 5 peat contents and 4 common moisture contents with two replications.
E.I. Ekwue et al.: Density-Moisture Relations of Two Trinidad Soils Obtained with a Soil Vibratory Compactor
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(a) (b)
Table 4. Analysis of variance for dry bulk density
Moreover, bulk density values decreased with increasing peat content as has been found in previous studies by Ohu et al. (1985), Ekwue and Stone (1994) and Ekwue and Stone (1995). As expected, values of mean density increased with increasing moisture contents up the range of 15% to 30% moisture contents compared. The analysis of variance (see Table 4) carried out on the results showed that the effects of the main experimental factors of soil type, peat content, and moisture content of the soil were all significant in that order at 1% level. The F value for method of compaction was significant at the same level confirming that that the density values obtained with the soil vibratory compactor were significantly lower than those obtained from the standard Proctor test, although the values were close.
In addition, the most significant interactions that affected soil density are those between soil type and peat content, soil type and moisture content, as well as peat content and moisture content. These are considered below.
The interaction between soil type and peat content (see Figure 4a), showed that although bulk density decreased with peat content for the two soils, the decrease was more dramatic for Talparo soil than the Piarco sandy loam soil as the peat content increased. Ekwue et al. (2014) found that peat reduces the cohesion in sandy soils and therefore makes them more compactible. They also found that peat increases the cohesion in clay soils and make them less compactible. The incorporation of peat to decrease soil compactibility (as measured with bulk density) will therefore be more beneficial in clay rather than sandy soils. The interaction between soil type and peat content (see Figure 4b) and that between peat content and moisture content (see Figure 4c) showed that increase in bulk density with increasing moisture contents was greater in Talparo soils and also in soils with greater peat content more than those in Piarco sandy soil and soils with lower peat contents. In these latter plots, it can be seen that although bulk density was lower for Talparo clay and soils with high peat contents, as the moisture content in the soils increased, the values of bulk density converged. The effect of clay or peat content in decreasing the bulk
density during soil compaction was higher at lower moisture contents and declined as the moisture content of the soils increased. A major reason for this is that at the range of moisture contents compared for the two soils (15% to 30%), the moisture contents of Talparo clay soil with different peat contents were still below the optimum and therefore the bulk densities were still rising (Figure 2), while those for the Piarco sandy loam were between the rising or falling limbs of the curves.
Figure 4. Interaction effects between (a) soil type and peat content (b) soil type and moisture content and (c) peat content and
moisture content on dry bulk density
4.4 Relationships between Dry Bulk Density and the
Experimental Factors
For each method of compaction, values of dry bulk density for the two soils with the five peat contents at the soil moisture contents were used to generate a multiple regression linear equation that could be used to predict bulk density. The two Equations (1) and (2) are:
For Proctor Test: ρb = 1.95 - 0.0170 CL (%) - 0.025 Pt (%) + 0.006 MC (%), R2 = 0.935, N = 68 (1)
Student ‘t’ 66.21 -27.15 -14.65 6.99
E.I. Ekwue et al.: Density-Moisture Relations of Two Trinidad Soils Obtained with a Soil Vibratory Compactor
where: ρb = dry bulk density (t m-3); CL = clay content (%) Pt = peat content; MC = moisture content; R2 = coefficient of determination; N = number of observations
The signs of the experimental factors in the equations above confirm how the factors affected the soil dry bulk density. The multiple coefficients of determination (R2) for the two equations were significant at 1% level. The Student ‘t’ values for all the experimental factors were significant at 1% level. The relative ‘t’ values in Equations (1) and (2) for all the factors also confirmed that the most important factor that affected soil densities in the Proctor test soil vibratory compactor tests were soil type, peat content, and soil moisture content for testing the soil in that order. 5. Conclusion
The study involved comparing density values from a soil vibratory compactor to those obtained using the standard Proctor test. Soil samples from two Trinidad soils incorporated with peat at five levels were tested with varying moisture contents using the standard Proctor method and with the soil vibratory compactor. It was found that the density and the maximum density values of soils obtained with the soil vibratory compactor were lower but within 0.02 to 0.06 t m-3 of those obtained using the Proctor test. The objectives of the study have been met. The following can be concluded from the study:
1. During testing, it was discovered that the constructed soil vibratory compactor is user friendly and easy to operate.
2. The constructed soil vibratory compactor is suited for laboratory testing of maximum density for most soils with different properties like peat and moisture contents, and
3. Density and maximum density values produced for the test soils were consistent and are very close to those obtained with the standard Proctor test.
References:
ASTM (2006) ASTM Standards: D 4253 – 00: Standard Test
Methods for Maximum Index Density and Unit Weight of Soils
using a Vibratory Table, ASTM International, West Conshohocken, PA USA.
ASTM (2007), ASTM Standards: D698-07: Standard Test Methods
for Laboratory Compaction Characteristics of Soil Using
Standard Effort, ASTM International, West Conshohocken, PA USA.
ASTM (2017), ASTM Standards: D7028 – 17: Standard test
method for particle-size distribution (gradation) of fine-grained
soils using the sedimentation (hydrometer) analysis, ASTM International, West Conshohocken, PA, USA.
BSI (1990), BS 1377, Part 4: Soils for Civil Engineering Purposes.
Compaction Related Tests, British Standards Institution, London.
Dobry, R. and Whitman, R.V. (1973), “Compaction of sand on a vertically vibrating table”, In: Selig, E.T. and Ladd, R.S. (Eds.), Evaluation of Relative Density and its role in Geotechnical
Projects Involving Cohesionless Soils, ASTM STP523, Baltimore, pp. 156-170.
de Kimpe, C.R., Bernier-Cardou, M. and Jolicoeur, P. (1982), “Compaction and settling of Quebec soils in relation to their soil-water properties”, Canadian Journal of Soil Science, Vol.62, No.1, pp.165-175.
Ekwue, E.I., and Stone, R.J. (1994), “Effect of peat on the compactibility of some Trinidadian soils”, Journal of
Agricultural Engineering Research, Vol.57, pp.129-136. Ekwue, E.I., and Stone, R.J. (1995), “Organic matter effects on the
strength properties of compacted agricultural soils”, Transactions of the ASAE, Vol.38, No.2, pp.357-365.
Ekwue, E.I., Stone, R.J., Maharaj, V.V., and Bhagwat, D. (2005), “Thermal conductivity and diffusivity of four Trinidadian soils as affected by peat content”, Transactions of the ASAE, Vol.48, No.5, pp.1803-1815.
Ekwue, E.I., Birch, R.A., and Chadee, R. (2014), “A comparison of four instruments for measuring the effects of organic matter on the strength of compacted agricultural soils”, Biosystems
Engineering, Vol.127, pp.176-188. Felton, G.K. and Ali, M. (1992), “Hydraulic parameter response to
incorporated organic matter in the B-horizon”, Transactions of
the ASAE, Vol.35, pp.1153-1160. Leonard, L., Ekwue, E.I., Taylor, A., and Birch, R. (2019),
“Evaluation of a machine to determine the maximum bulk density of soils using the vibratory method”, Biosystems
Engineering, Vol.178, pp.109-117. Ohu, J.O., Raghavan, G.S.V., and Mykes, E. (1985), “Peatmoss
effect on the physical and hydraulic characteristics of compacted soils”, Transactions of the ASAE, Vol.28, pp.420-424.
Prochaska A. and Drevich, V. (2005), “One-point vibrating hammer compaction test for granular soils”, Proceedings of Geo-
Frontiers. Advances in Pavement Engineering, Austin, TX, pp.1-15. Accessed on February 18, 2020 from: https://www.rjh-consultants.com/sites/www.rjh-
Ditzler, C. (2017), Revision of the Classification of the Soils of
Trinidad and Tobago Based on Keys to Soil Taxonomy, 12th Edition, Accessed on December 3, 2019 from: https://sta.uwi.edu/ffa/sites/default/files/ffa/USDA%20soil%20Taxonomy%20Upgrade-Trinidad%20and%20Tobago.pdf
Stone, R.J. and Ekwue, E.I. (1993), “Maximum bulk density achieved during soil compaction as affected by the incorporation of three organic materials”, Transactions of the ASAE, Vol.36, No.6, pp.1713-1719.
Suryakanta, P. (2014), Factors Which Affect Field Compaction or
Degree of Compaction. CivilBlog.Org, Accessed April 24, 2016 from: http://civilblog.org/2014/02/04/5-factors-which-affect-field-compaction-degree-of-compaction/.
Thompson, P.J., Jansen, I.J., and Hooks, C.L. (1987), “Penetrometer resistance and bulk density as parameters for predicting root system performance in mine soils”, Soil Science
Society of American Journal, Vol.51, pp.1288-1293. Waldemar S.S, and Lechocka, P. (2016), “The influence of a
laboratory testing method on the index of density of sand”, Proceedings of the World Congress on Civil, Structural, and
Environmental Engineering (CSEE’16), Prague, Czech Republic – March 30 – 31, 2016. Accessed on April 23, 2018 from: https://avestia.com/CSEE2016_Proceedings/files/paper/ICGRE/114.pdf
Walkley, A. and Black, I.A. (1934), “An examination of the effect of Degtjareff method for determining soil organic matter and a proposed modification of the chromic acid titration method”, Soil
Science, Vol.37, pp.29-38.
E.I. Ekwue et al.: Density-Moisture Relations of Two Trinidad Soils Obtained with a Soil Vibratory Compactor
10
Authors’ Biographical Notes:
Edwin I. Ekwue is currently Professor and Dean, Faculty of
Engineering at The University of the West Indies, St. Augustine,
Trinidad and Tobago. He is also Coordinator of the Bio-systems
Engineering Programme and was a past Head of the Department
of Mechanical and Manufacturing Engineering. His specialties are
in Water Resources, Hydrology, Soil and Water Conservation and
Irrigation and Drainage Engineering. His subsidiary areas of
specialisation are Structures and Environment, Solid and Soil
Mechanics, where he has teaching capabilities. Professor Ekwue
has served as the Deputy Dean of Undergraduate Student Affairs
and Postgraduate Affairs and Outreach, as well as the Chairman
of Continuing Education Committee, and as the Manager of the
Engineering Institute in the Faculty of Engineering.
Aliyah Abasali is a Graduate of the Mechanical Engineering
Programme. She is desirous of reading for a Master’s degree in
Mechanical Engineering. Currently, she is employed with the On-
the-Job Training Programme as a Teacher’s Aide. She also helps
with managing a food business owned by her family.
Carlotta Bharat is an Instructor in the Department of Mechanical
and Manufacturing Engineering at The University of the West
Indies, St Augustine, Trinidad and Tobago. She has a BSc. in
Mechanical Engineering with a Minor in Biosystems, and is
currently a candidate for an MPhil degree in Agricultural
Engineering with a focus on Hydroponics. Her areas of interest
and teaching capabilities include Soil and Water Conservation,
Irrigation and Drainage Engineering.
Robert A. Birch is Lecturer in the Department of Mechanical and
Manufacturing Engineering at The University of the West Indies, St
Augustine, Trinidad and Tobago. He is a registered Professional
Engineer (R.Eng) and Project Management Professional (PMP)
with over twenty years of industrial and teaching experience. He
has a BSc. (Eng) and MPhil in Agricultural Engineering and a
PhD in Mechanical Engineering from The University of the West
Indies. Dr. R. Birch is a Fellow of the Institution of Agricultural
Engineers (UK) and his interests are in Bio-systems Engineering
with particular attention to the application of computer-aided
design (CAD) and computer-aided engineering (CAE) in the
development of innovative crop production and agro-processing
machinery.
S.C. Nwaneri et al.: A Low-Cost IoT Based Neonatal Incubator for Resource Poor Settings 11
A Low-Cost IoT Based Neonatal Incubator for Resource Poor Settings
Solomon C. Nwaneri a,Ψ, Jesubori W. Sojobi b, Aderounwi O. Oyelade c, Beatrice N. Ezenwa d, Oluwaseyi J. Balogune, and Ugochi C. Uregbulamf
a,b,c,e,f Department of Biomedical Engineering, Faculty of Engineering University of Lagos, Nigeria. aEmail: [email protected], [email protected]
d Department of Paediatrics, College of Medicine, University of Lagos, Nigeria; Email: [email protected]
Ψ Corresponding Author
(Received 24 July 2019; Revised 04 May 2020; Accepted 21 May 2020)
Abstract: Preterm births in resource poor countries are characterised by high infant mortality. The high cost and non-
availability of conventional neonatal incubators are considered to significantly affect efforts aimed at mitigating this
problem. In this paper, a low-cost Internet of Things (IoT) based neonatal incubator with phototherapy blanket is
presented. The device was constructed using a wooden box with a dimension of 33 × 20 × 18 inches, a heating
element, a relay, a liquid crystal display (LCD) module, an l2C module, control buttons, a light emitting diode (LED),
220 Ω resistors, 5 volts’ power supply, transparent 2 mm thick acrylic sheet, a mattress, Wi-Fi module and LED based
phototherapy blanket. An IoT platform was developed for real-time monitoring of temperature and humidity of the
incubator which can be accessed by a password protected graphical user interface (GUI) application developed using
C programing language. Modelling and simulation of the incubator environment based on standard thermodynamic
principles were performed using Python programming language. A relatively stable temperature and humidity suitable
for an infant was observed in the developed device. The IoT platform was effective in monitoring the temperature and
humidity of the device. Incubator temperature attained steady state in 200 seconds. The environmental conditions were
found to be suitable for a neonate. The device was effective for real-time monitoring of environmental conditions in the
incubator.
Keywords: Internet of Things, Humidity, Neonatal Incubator, Phototherapy Blanket, Smart Medical Devices
1. Introduction
Preterm births account for a significant proportion of child births globally. According to the World Health Organisation (WHO), about 15 million babies born yearly are preterm (WHO, 2018). Complications from preterm births are mostly responsible for high infant mortality and morbidity especially in low income countries. Majority of preterm deaths are caused by lack of simple essential care and poor thermoregulation (Pandya et al., 2017). Thermoregulation, a mechanism that regulates body temperature plays a unique and crucial role in the nurturing and development of a baby (Shelke et al., 2017). However, the absence of thermoregulation in preterm babies leads to hypothermia, and other health complications or even death if not adequately handled. Neonatal incubators are essentially designed to improve their chances of survival. Accordingly, neonatal incubators provide a controlled environment for neonates by regulating environmental conditions such as temperature, humidity and ventilation. This system mimics the mother’s womb where complete embryonic development should take place. Incubators
are made of a rigid box-like enclosure that provides a closed and controlled environment for the sustenance of premature babies (Sowmiya et al., 2018). Amongst the important benefits of a neonatal incubator is the early detection of potential life-threatening events (I-smac, 2017). The average normal axillary temperature of an incubator is 37°C while a temperature of 38°C (100°F) or greater, as measured by a rectal thermometer, represents a fever (Mackowiak, 1992). Normal axillary temperature is between 36.5°C and 37.5°C (WHO, 1997).
The origin of incubators is linked to Stephen Tarnier, a French obstetrician who designed the first neonatal incubators in a form similar to chicken incubators housing several infants (Baker, 2000). However, Tarnier’s incubator had no temperature and ventilation control system. Alexander Lion, in the 1890s developed a large metal apparatus equipped with a thermostat and an independent forced ventilation system, the Lion incubator was designed to compensate for less than optimal nursing or environment (Baker, 2000). Alexander Lion’s incubator includes a large metal
ISSN 0511-5728 The West Indian Journal of Engineering
Vol.43, No.1, July 2020, pp.11-20
S.C. Nwaneri et al.: A Low-Cost IoT Based Neonatal Incubator for Resource Poor Settings
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apparatus, a thermostat regulated heater and an independent forced ventilation system (Ann, 2004). Several other types of incubators have evolved over the years with a variety of innovations recorded.
A number of innovations have been introduced to enhance the effectiveness and efficiency of an incubator. Bouattoura et al. (1998) proposed an active humidification system and developed an algorithm using a combination of optimal control theory and dynamic programming approach. Furthermore, an enhanced temperature control system was designed, using thermistors and incorporating a combination of Pulse Width Modulation (PWM) and simple ON-OFF control system. Incubators have become more sophisticated since late 20th century with the use of microprocessors. Amadi et al., (2007) developed a recycled incubator technique (RIT). Tisa et al. (2012) designed an enhanced temperature control system incorporating a combination of Pulse Width Modulation (PWM) and simple ON-OFF control system, using thermistors as temperature sensors. These developments in the 21st century generally improved the focus on better designs for neonatal incubators. Also, Sun (2015) designed and implemented an infant incubator intelligent control to address the problem of cost and lack of spares for incubators in resource poor settings. Recent innovations in the design of incubators include the incorporation of IoT systems for direct communication of the doctor and mother with the incubator (Huang et al., 2015).
The current method for monitoring the baby's temperature is with a thermistor and a controlled heating unit, but it cannot account for the water lost through the skin, which is critical to maintain the neonate for the first 7 to 10 days after birth to prevent dehydration. In preterm infants, hypothermia increases morbidity and mortality. It is therefore necessary to maintain an appropriate environmental temperature in the delivery room (Robert et al., 2018). Humidity is one of the four primary variables which must be controlled during incubation - the others being temperature, ventilation and movement (or turning). In addition, Jaundice is a common disease that affects preterm infants. Approximately 80% of infants become jaundiced during the first week of life (Woodgate and Jardine, 2011). Jaundice is due to excessive accumulation of bilirubin known as Hyperbilirubinemia, a product of the degradation of red blood cells, in the blood. Hyperbilirubinemia, may also indicate liver or gall bladder disease (Kelnar et al., 1995).
Equipping the incubator with a phototherapy blanket could be useful in the treatment of jaundice in preterm infants (Rose, 2000). With the phototherapy blanket, there would not be a need to attach a phototherapy light to the incubator. Phototherapy blankets perform a better function than phototherapy lights because they cover larger surface areas. Phototherapy breaks down bilirubin to a water-soluble form that could be excreted in the urine (Vreman, 2004). Prior to phototherapy, sunlight was used to treat jaundice. However, long exposure to sunlight is associated with various levels of risks to the newborn. Phototherapy blankets are more effective because they can be used both indoors and at night (Aeroflow, 2011). Potentially harmful ultraviolet and infrared energy are filtered out in a phototherapy blanket.
Traditional incubators lack real-time remote monitoring features which make them very difficult for busy parents and care givers to monitor the health condition of their babies. However, modern incubators could be optimised with the Internet of Things (IoT) technology. The IoT is a network-based system that enables machine to machine (M2M) communication between various devices (Sarmah et al., 2017). Automatic identification of devices within the network and information sharing are achieved by the use of the IoT (Sun, 2015). Physical and virtual objects are linked by an internet-built network with various sensors and devices on the basis of exploiting data with advanced communication (Verdouw and Beulens, 2013). The IoT obtains the object’s information using cloud computing and intelligent computing technique (Wang, 2011).
This paper focuses on the design of a low cost smart neonatal incubator for monitoring parameters like temperature, humidity, amount of gas, bilirubin level in the baby, pulse rate of the baby and light inside the incubator. The device also sends these details to an online information storage platform where any mobile phone that can provide security information for the website can easily access. This study improves existing designs with the incorporation of an IoT system with a LED designed phototherapy blanket. 2. Materials and Method
2.1 Materials
The device consists of a wooden box, a heating element, a relay channel, an LCD module, an l2C module, control buttons, a female header, a 5 mm LED and a neonatal incubator. Table 1 shows the materials and reasons for their selection. Cost, availability and safety
Table 1. Materials Selection
S/N Part Material Description Reason for choice of material
1. Incubator top 4 × 8 feet transparent glass, 2 mm thick acrylic sheet, and wood Cheap and readily available
2. Angle Brackets Aluminum Aluminum is strong and durable
3. Table stand Wood and Aluminum Cheap and readily available
4. Table top 18 mm medium density fiber sheet Strong, cheap and readily available
5. Mattress Foam Biocompatibility
6. Blanket Cotton Towel fabric Towels are soft and furry
S.C. Nwaneri et al.: A Low-Cost IoT Based Neonatal Incubator for Resource Poor Settings
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Table 2. Design Requirements
S/N Characteristics Description
1. Power • The device requires a 220 V, 50 Hz clean and stable AC power supply.
2. Temperature • The device needs to operate at a suitable temperature range of between 30°C and 35 °C ambient temperature.
3. Humidity • The relative humidity of the incubator should be between 40 % and 75%.
4. Safety • The incubator will not expose the baby to any form of electrical shock.
• The device will be properly ventilated.
• Biocompatibility of the materials that make contact with the baby. The materials should not cause injury or any form of harm to the baby.
5. Cost • The device should be affordable to majority of hospitals/users in resource poor settings.
• Maintenance costs should be affordable.
6 Maintainability • The incubator should be easy to maintain.
considerations were the main criteria for material selection. The design requirements of the device are depicted in Table 2.
The incubator is made of rectangular box with a glass cover at the top and circular openings at the sides of the boxes with a communication system incorporated. It is to provide information to the medical personnel and caregivers. The hardware and software modules of the device are discussed.
2.3 Device Design and Implementation
2.3.1 Hardware Design and Implementation
The 3D CAD design of the device is presented in Figure 1. All dimensions of the CAD design are in millimeters. The device was designed with a dimension of 830 × 450 × 500 mm with a circular space with a diameter of 100 mm and a top cover of 774 x 250 mm. Figure 2 shows a picture of the prototype device. The incubator was designed using a rectangular box made of glass and wood of 33 × 20 × 18 inches. With a door at the top made of an acrylic material, the incubator also has an access port of 3.5 inches diameter enclosed by an elastic leather band. The hardware is supported by a wooden stand, and two pairs of wheels for easy transportation of the device. A mattress was placed inside the incubator.
A block diagram of the incubator is shown in Figure 3. The incubator is powered by 240 V mains electricity supply and regulated by a 5V switching power supply. The heating element made of a metallic plate with a dimension of 8 cm × 1.8 cm is heated once the device is powered on. Heat generated by the heating element keeps the surface temperature warm. Temperature and humidity control are necessary in a neonatal incubator to provide a safe and conducive environment for the infants. DHT11, a simple, low-cost digital temperature and humidity sensor was used for this purpose. Operating within a voltage range of between 3V and 5V, the sensor is capable of measuring temperature of (0oC - 50oC) and humidity (20% - 90%). The sensor transmits its signals to an 8-bit microcontroller (PIC 18F4520). The microcontroller consists of an on-chip eight channel, 10-bit Analog-to-Digital Converter (ADC) which converts the analog signal to digital. The amplified and conditioned sensor signals are fed to the microcontroller.
The temperature and humidity values are displayed on a liquid crystal display (LCD) module capable of showing 16 characters in 6 lines.
Figure 1. 3D CAD Design of the incubator
Figure 2. A Picture of the Prototype
.
Figure 3. Block Diagram of the Incubator
S.C. Nwaneri et al.: A Low-Cost IoT Based Neonatal Incubator for Resource Poor Settings
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The surface temperature is measured with a surface mounted thermistor (NTC temperature sensor) and relative humidity is measured with the help of a moisture holding component between two electrodes through the measurement electrical resistance between the two electrodes in order to detect the water vapour content. For temperature regulation, a precision integrated circuit temperature sensor, LM35 was used to measure temperature in the range of -40oC to +125oC which is sufficient for the targeted body temperature range and provides an analogue output with a linear transfer function given by:
Vout = 10mV/oC X T (1)
where, Vout = Output voltage; T = the Temperature in °C
Temperature is controlled by turning on an alarm whenever the temperature exceeds the prescribed temperature. Consequently, the heater gets turned off through the mobile app. The app also helps to continuously monitor the temperature in order to notify the care giver in case of an emergency (Sowmiya et al., 2018). The IoT system works with sophisticated microprocessor that regulates temperature and humidity of the incubator. It also sends the information from the incubator to a web platform in periods almost in real time. A circuit diagram for detection and monitoring of the incubator is shown in Figure 4.
Figure 4. Circuit Diagram for the Detection and Monitoring of the Incubator
2.3.2 Control Logic of the Incubator
The system is a closed loop system controlled by the NodeMCU and powered by a 220 V AC supply which is supplied to the heater once the switch is closed. Conversely, the relay is fed with a 5V DC supply. The temperature sensor (DHT11) senses the temperature within the device and as soon as it detects a temperature
beyond the set point, the relay cuts off to disconnect the heater with minor temperature fluctuations which can only be detected by smart sensors. The control system of the incubator is illustrated in Figure 5.
The NodeMCU is the IoT platform programmed in C programming language. When a targeted temperature is set from the keypad the microcontroller switches on the heater by sending 5 volts to pin 13 which triggers the relay. The program monitors the temperature reading from the temperature and humidity sensor every 0.5 seconds. Once the temperature exceeds the targeted temperature by 0.5 degrees the program switches pin 13 off thereby turning off the heater. Besides, once the temperature drops by 0.5 degrees, the program switches on the heater again and the cycle goes on. The NodeMCU is connected to a webserver via the Wi-Fi to update its own data, and to check for remote commands sent to it. A website was designed using HTML5, which displays the status of the status of the incubator, by connecting to a remote webserver and retrieving the latest report left there by the incubator.
Figure 5. Control system of the incubator
2.3.3 Phototherapy Blanket
The incubator is equipped with a phototherapy blanket, for the treatment of neonatal jaundice. The phototherapy blanket is a covered pad consisting of flexible LEDs light strip which are considered suitable and comparable to conventional phototherapy lamps for the treatment of neonatal jaundice (Kumar et al., 2010). The LED light strips were attached to the cotton fabric material. When powered, the UV LEDs will emit light of between 395 - 405 nm wavelengths. The UV LEDs are powered by a built in 5V DC supply adapter. The phototherapy blanket is shown in Figure 6.
Figure 6. The phototherapy blanket under construction
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2.3.3 The IoT System Implementation
The device was designed with an open source IoT platform, NodeMCU which is considerably preferred over other boards because of its low cost, low power consumption, reduced size and integrated support of Wi-Fi. The NodeMCU is from the ESP8266 family (Bento, 2018). Ubidots cloud is an easy and affordable means of IoT data analytics, which changes the sensor data into information. This storage platform also provides access to shared pools of data, which is often accessible only over the internet. A block diagram of the IoT system is shown in Figure 7.
Figure 7. Block diagram of the IoT system
2.3 Device Testing and Validation
Testing of the device was performed after the integration of the incubating system, IoT system and the Phototherapy blanket: Voltages and other electrical signals were measured and were absent in all contact areas of the human subject. The device was tested on plastic dummies with the temperature set to a target temperature of 24oC. The time it takes to reach the targeted temperature depends on the voltage supply which is proportional to the targeted temperature. The LCD displays the temperature as shown in Figure 8.
Figure 8. Real-time display of parameters on LCD
The SSID and IP address of the Wi-Fi is displayed on
the LCD as indicated in Figure 8. An administrator or user can access information to determine the status of the device logging on to the device as shown in Figure 9 with the target temperature is set. User authentication is through the use of username and encrypted passwords either as admin or guest as indicated in Figure 10. The IoT device renews the information sent from the incubator to the phone every minute. The IoT platform was effective in monitoring the conditions in the incubator.
Figure 9. Login Page of the IoT system
Figure 10. Wi-Fi connection settings on the website
In accordance with the Failure Modes and Effects
Analysis (FMEA) we determined the risks associated with the use of the device. Probable risks and their severity were calculated in accordance with FMEA. Risk Priority Number (RPN) for each risk was obtained by the multiplication of the probability of failure (PF), severity of effect (S) and probability of detection of an existing defect (D) (Abike et al., 2010) as shown in Equation (2):
RPN = S X P X D (2)
The evaluation metrics used in this study is presented in Table 3. The FMEA was calculated in Table 4 which also includes preventive measures included in the design to mitigate the effects of the failure modes and risks associated with the use of the device.
2.3 Device Modelling and Simulation
Temperature and heat loss calculations are important because the incubator’s internal environment temperature must be warmer than the external
S.C. Nwaneri et al.: A Low-Cost IoT Based Neonatal Incubator for Resource Poor Settings
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Table 3: Probability-Severity-Detection Matrix
Variable Severity Probability of Occurrence Detection
Very high Death (10) Very High: Failure is inevitable (10) Impossible to be detected (10)
High Severe injury (8) High: Failure is Possible to repeat (8) Difficult to be detected (8)
Low Minor injury (3) Low: Relatively few failures (3) Easy to be detected (3)
Very Low Very minor injury (1) No injury (0)
Very /low: Less likely to occur (1) unlikely to occur (0)
Almost certain to be detected (1)
Table 4: Failure Mode Effects Analysis for Incubator
S/N Risks Detection
(D)
Severity
(S)
Probability of
occurrence (P)
RPN Preventive Measures Taken
1. Over or under-heating of the infant due to thermostat failure, dehydration
3 8 3 72 Temperature sensors/other components operate with low DC voltages (3V – 5V)
2. Electric Shock to the infant 10 10 1 100 Components operate with low voltages (3V – 5V)
3. Failure of alarm in the event of deviation of temperature from set values
1 5 3 15 Frequent monitoring of device
4. Hypothermia of infant due to low temperatures
3 8 3 72 Remote monitoring capability of device will help address this. Regular
5. Device falls unexpectedly causing trauma to infant
1 8 1 8 Device is very balanced and unlikely to fall. Instructions to ensure it is properly placed.
6. Doors unable to open easily causing the infant to be trapped inside the device
1 6 1 6 Door at the top freely opens. Hinges can easily be dismantled in the event of any failure.
7. Air ceases to flow through the device due to mechanical failure
1 6 1 6 Adequate provision of hole with diameter 3.5 inches and enclosed by an elastic leather band.
8 Inadequate humidity in the system 1 6 3 6 Regular monitoring needed.
environment. The body temperature of the baby should also be higher than the incubator’s internal environment. Heat losses through various forms including conduction, convection and radiation are minimal. Conductive heat loss between the infant and foam is minimal as the foam is made of an insulator. Equations (3), (4) and (5) show temperature and heat calculations for the device. The equations reveal that heat entering the incubator and heat generated by the incubator are equivalent to heat consumed by the incubator with the baby and heat lost by the incubator to the environment. This obeys the first law of thermodynamics which states that:
The change in the internal energy of a system, ∆U is equal to
the heat added to the system, Q minus the work done by the
system, W as shown in Equation (3):
∆U = Q - W (3)
Notations: ∆θincubator = change in temperature inside the incubator ∆θheater = change in temperature outside the incubator ∆θbaby = change in temperature of the baby mincubator = mass of the incubator mbaby = mass of the baby mheater = mass of the heater c = hear capacity heatin = heat entering the incubator heatgen = heat generated by the incubator heatconsumed = heat consumed or absorbed by the incubator heatlost = heat lost by the incubator to the environment
Equation (3) is further simplified into equations (4) – (6). Total heat energy is conserved. Therefore, regulation of the heat generated by the incubator is necessary to ensure the infant within the device does not have too much heat or lose too much heat.
The temperature inside the neonatal incubator depends on both physiological and environmental variables. Simulation is based on the equilibrium of metabolic heat generation in the body (M) and the various methods of heat transfer including conduction, convection, evaporation and radiation between the skin, phototherapy blanket and the environment. Figure 11 shows the block diagram of the heat exchange model which is similar to previous study. The major difference is the inclusion of the phototherapy blanket (Delanaud et al., 2019). The model was partitioned into four homogenous sections including the incubator airspace, incubator wall, the phototherapy blanket and the mattress.
S.C. Nwaneri et al.: A Low-Cost IoT Based Neonatal Incubator for Resource Poor Settings
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Figure 11: A block diagram of the heat exchange in the incubator
Source: Abstracted from Delanaud et al., (2019)
Heat exchange models well reported in literature
were adopted for this work (Delanaud et al., 2019; Decima et al., 2012). The governing differential equation for heat exchange in incubator is given as:
Ρ *V * Cv * dTa/dt = M + Hheater + HRP - Hstr (7)
Where ρ (Kgm-3) is the density of the air, V(m3) is the volume of the incubator and Cv(JKg-1K-1), Ta(K) the temperature of the incubator, Hheater is the electrical power of heating element, HRP is the heat energy supplied by LED phototherapy blanket, Hstr is the heat energy loss from the incubator structure to the environment and M is the metabolic heat generated by the infant’s body. Metabolic heat in neonate body can be partitioned as shown in equation (8)
M = Hc + Hk + HE + HCR + HEB + HR (8)
Here Hc is the convective heat transfer from the skin surface to the moving air in the incubator, HR is the radiant heat between the infant’s skin to distant cold objects, HE is the skin evaporative heat loss, Hk is the heat conducted from the skin to the mattress, HEB is the evaporative heat loss that is due to breathing and HCR is the convective heat loss through the respiratory tract. Metabolic heat production can also be calculated using Equation (9)
M = minf (0.052Pinf + 1.64) /Vinf (9)
Here, minf (Low Birth Weight (LBW) < 2.5Kg) is the mass of the infant, Pinf is the baby’ age (days) and Vinf is the volume of the infant’s body. Equation (10) is the compartmentalised equation for heat loss to the incubator structure.
Hstr = Hwood + Hglass + Haluminum + Hrubber (10)
Where Hwood , Hglass , Haluminum and Hrubber are the heat lost in the incubator to wood, glass, aluminum and rubber respectively.
Hwood = AwUw (Ta – To) (11)
Here Aw is the net area of the wooden structure, Uw is the heat transfer coefficient of the wood, Ta is the inside
design temperature and To is outside temperature. Similarly, the heat lost in Hgrass, Hrubber and Haluminum takes the form of Equation (11) but with different values of areas and heat transfer coefficients. Heat loss due to infiltration and ventilation is not considered. HRP is the radiant heat energy supplied by the phototherapy blanket. Simulation was performed in Python programming language based on the following parameter values indicated in Table 5.
Table 5. Parameters and Corresponding Values
Parameter Values
minf , mass of infant 2,500 g
Pinf , the baby’ age (days) 1 day
V(m3) is the volume of the incubator 0.25
Cv , Specific heat capacity of air 1005 J/Kg K
Ta , the inside design temperature 297 K
ρ(Kgm-3), the density of the air 1.225 Kg/m3
V, Volume of incubator design 0.18675 m3
Thermal conductivity of rubber 0.163 W/m K
Hwood, Heat transfer coefficient of wood 1.613 W/m2 K
Hglass, Heat transfer coefficient of glass 5.28 W/m2 K
Haluminum, Heat transfer coefficient of aluminum 3.6 W/m2 K
Awood , Area of wood 0.511 m2
Aglass, Area of glass 0.6444 m2
Arubber, Area of rubber 0.01571 m2
UV LEDs 395 – 405 nm
Heating power of LED blanket 2(8.64)=17.28W
3. Results and Discussions
3.1 Modelling Temperature versus Time
Simulation results were obtained and briefly discussed. The relationship between incubator temperature and time is demonstrated by varying the conditions of the heater H, and the phototherapy blanket, P. The plot of incubator temperature against time of operation is shown in Figure 12. When both H = 80W (maximum value of the heating element) and P is on, the incubator temperature is greater than 37 degrees Celsius. If H is switched off and P is operating, the incubator temperature is less than 32 degree Celsius.
Figure 12. Temperature Versus Time (Case 1)
S.C. Nwaneri et al.: A Low-Cost IoT Based Neonatal Incubator for Resource Poor Settings
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The most suitable temperature for full-term and
preterm infants is obtained when H = 20W and P on (34.5 degree Celsius after 200 seconds) as shown in Figure 13.
Figure 13. Temperature Versus Time (Case 2)
The behaviour of incubator temperature is examined
for various H values while P is switched off. We observed in Figure 14 that at H = 45W the incubator temperature remained constant at 36 degree Celsius from time 200 seconds and above. For the three (3) cases considered, incubator temperature attained steady state in 200 seconds (less than 4 minutes).
Figure 14. The plot of Incubator temperature against Time
(Case 3)
3.2 Device Testing Results
Physical parameters within the infant incubator were measured by smart sensors with no infant in the device. To observe the behavior of the system, the temperature and humidity of the incubator readings were taken at every 5 minutes’ interval. To begin the test, the temperature was set to 25oC and a temperature sensor was used to observe the change in temperature. The relationship between the device temperature and time is
displayed in Figure 15. The temperature is held between 24oC and 26oC under the control thermistor in the infant incubator that measures and regulates the temperature within the set value.
In Figure 16, the relationship between the device humidity and time is presented. The relative humidity is between 48 % and 61 %. This range of temperature and relative humidity are suitable for the baby. These data and experiment show that the intelligent infant incubator system works well based on the design.
Figure 15. Temperature versus Time
Figure 16. Humidity versus Time
3.3 Discussion
The expensive nature and limited features of conventional neonatal incubators underscores the need for a low cost, smart infant incubator which was developed in this study for resource poor settings. Several innovative features have been incorporated to the device to assist physicians and care givers in monitoring the environmental conditions within the device remotely. The effectiveness of the IoT platform in monitoring the temperature and humidity of the device was demonstrated. The IoT has been extensively applied in the interconnection of medical devices and sensors by assisting physicians in accurately monitoring the health of their patients (Dridi et al., 2017). Although security is
S.C. Nwaneri et al.: A Low-Cost IoT Based Neonatal Incubator for Resource Poor Settings
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a concern in IoT systems, the benefits far outweigh the disadvantages. A two-factor authentication system based on username and encrypted password protection which was implemented in this study will to a large extent provide basic security.
A comparison of the cost of developing the device and other related neonatal incubators shows our device to be relatively cheaper. The market prices of similar incubators are between $2,000.00 and $3,000. The device was produced at a lower cost of $390, which makes it suitable for resource poor settings. The high cost of medical devices manufactured in developed economies is often too expensive for small and medium sized hospitals in resource limited settings. Moreover, the limited resources for device training and repair make advanced equipment difficult to use (Blue, 2014).
Analysis of the results shows that the time taken for the incubator to reach the target temperature is 5 minutes with the initial temperature at 20. The analysis also shows a fluctuation within 24 to 26 temperature range, and the thermistor cuts off the heater once the desired temperature is exceeded. The temperature later reduces to the set temperature. This process happens continuously and causes a variation between the temperature ranges of 24 to 26. The humidity also varies between 48% and 61% due to the varying temperature. Another unique feature of the incubator is the phototherapy blanket, for the treatment of neonatal jaundice. In addition to the other benefits of a conventional neonatal incubator, this device is suitable for the treatment of neonatal jaundice in premature infants. A significant reduction in infant mortality could be achieved in developing countries with the mass production of the device. The incorporation of the phototherapy blanket to the device will no doubt reduce infant morbidity and mortality.
4. Conclusion
In this paper, an IoT based neonatal incubator was developed. This work provides solution to the challenges of untimely death of neonates and also treats jaundice at the same time at an affordable price. The system controls the temperature and humidity of the environment, and provides a means of monitoring and readjusting the values of the temperature and humidity of the environment of the baby and treating jaundice simultaneously.
References:
Abike, F., Tiras, S., Dunder, I., Bahtiyar, S., Uzun, O.A., and Demircan, O. (2010), “A new scale for evaluating the risks for In-Hospital Falls of Newborn Infants: A failure modes and effect analysis study’, International Journal of Paediatrics, http://dx.doi.org/10.1155/2010/547528 .
Amadi, H.O., Mokuolu, O.A., Adimora, G.N., Pam S.D., Etawo, U.S., Ohadugba, C.O., and Adesiyun, O.O., (2007), “Digitally recycled incubators: better economic alternatives to modern
systems in low income countries”, Annals of Tropical
Paediatrics, Vol.27, No.3, pp.207-214 Antonucci, R., Porcella, A., and Fanos, V. (2009), “The infant
incubator in the neonatal intensive care unit: unresolved issues and future developments”, Vol. 37, No. 6, pp.587-598.
Arpita, R., Saxena, K., and Bhadra, A.A., (2015), “Multibands dual linearly polarised 2$ antenna array for powering sensors in IoT System”, International Journal of Engineering Studies and
Technical Approach, Vol.1, No.4, pp.36-42. Baker, J.P. (2000), “The incubator and the medical discovery of the
premature infant”, Journal of Perinatology, Vol.20, pp.321-328. Bento, A.C. (2018), “IoT: NodeMCU 12e X Arduino Uno, Results
of an experimental and comparative survey”, International
Journal of Advanced Research in Computer Science and
Management Studies, Vol.6, No.1, pp.46-56. Blackburn, S. (1995), “Hyperbilirubinaemia and Neonatal
Jaundice”, Neonatal Network, Vol.14, No.7, pp.15-24. Blue, L. (n.d.) Report: Why 40% of Donated Medical Equipment
Goes Unused in Poor Countries, Available from: http://healthland.time.com/2012/08/06/report-why-40-of-donated-medical-equipmentgoes-unused-in-poor-countries/ [Last accessed on July 20, 2019].
Delanaud, S., Yassin, F.C., Durand, E., Tourneux, P., and Libert, J.P. (2019), ‘Can mathematical models of body heat exchange accurately predict thermal stress in premature neonates?” Applied Sciences, Vol.9, pp.1541: doi:10.3390/app9081541
Decima, P., Stephan, E., Pelletier, A., Ghyselen, L., Delanaud, S., Degrugilliers, L., Telliez, F., Bach, V., and Jean-Piere, L. (2012), “Assessment of radiant temperature in a closed incubator”, European Journal of Applied Physiology, Vol.112, pp.2957- 2968, doi:10.1007/s00421-011-2265-9
EBME (2010), “Baby Incubation, Incubators for Control of Temperature and Environment”, Medical and Clinical
Engineering. Medical Engineering Jobs and Discussion Forum, April.
Edward F. Bell (2018), ‘Servocontrol: Incubator and Radiant Warmer’, Available from: https://uichildrens.org [Last accessed on July 20, 2019].
Huang, T., and Sun, T.H. (2015), “Design and implementation of the infant incubator intelligent control”, The Open Automation
and Control Systems Journal, Vol. 7, pp. 2223 - 2229. Hull, D., and Wheldon, A. (1986), “Archives of disease in
childhood: Open or closed incubators”, Archives of Diseases in
Childhood, Vol 61, pp.108-109. Kelnar, C.J.H,, Harvey, D., and Simpson, C. (1995), The Sick
Karthi, N., Subramanian, S., Sravanthi, J., Gaddam, P., and Singh, S.N. (2010), “Light-emitting diodes versus compact fluorescent tubes for phototherapy in neonatal jaundice: controlled a multi-center randomised trial”, Indian Pediatrics, Vol.47, No.2, pp. 131-137.
Leduc, D., and Woods, S. (2000), “Temperature measurement in paediatrics”, Canadian Paediatric Society, Vol.5, pp.273- 276.
Mackowiak, W.S. (1992), “A critical appraisal of 98.6 degrees F, the upper limit of the normal body temperature, and other legacies of Carl Reinhold August Wunderlich”, The Journal of
the American Medical Association, Vol. 268, pp.1578-1580. Mittal, H., Mathew, L., and Gupta, A. (2015) “Design and
Development of an infant incubator for controlling multiple parameters”, International Journal of Emerging Trends in
Electrical and Electronics, Vol.11, No.5, pp.65-72. Moreno, I. (2020), “LED irradiance pattern at short distances”,
Applied Optics, Vol.59, No.1, pp.190-195. Pandya, D., Parmar, J., and Patel, A. (2017), “PIC Microcontroller
based baby incubator using sensors”, International Research
Journal of Engineering and Technology, Vol.3, pp.1906 -1910.
S.C. Nwaneri et al.: A Low-Cost IoT Based Neonatal Incubator for Resource Poor Settings
20
Rodriguez, R.J., Martin, R.J., and Fanaroff, A.A. (2002), “Respiratory distress syndrome and its management”, In: Fanaroff, A.A., and Martin, R.J. (2002), Neonatal-perinatal
Medicine: Diseases of the Fetus and Infant, 7th Edition, Mosby, pp.1001-1011.
Sarmah, A., Baruah, K.K., and Baruah, A.J. (2017), “A brief review on Internet of Things”, International Research Journal of
Engineering and Technology (IRJET), Vol. 4, pp. 879. Sarode, S.M.D., and Shelke, R.G. (2017), “Intelligent baby
incubator using solar”, International Journal of Research in
Applied Science and Engineering, Vol. 5, No.4, pp.2321-9653. Shelke, R.G., Sarode, D.S., and Mathpati, S.K. (2017), “Intelligent
baby incubator using solar’, International Journal of Research in
Applied Science and Engineering Technology, Vol.5, No.6, pp. 2223-2227.
Sowmiya, S., Smrithi, V., and Irin Loretta, G. (2018), “Monitoring of incubator using IoT”, International Research Journal of
Engineering and Technology, Vol.5, No.4, pp.635- 638. Tellaeche, A., Burgos-Artizzu, X.P., Pajares, G., Ribeiro, A., and
Quintanilla, C.F. (2008), “A new vision-based approach to differential spraying in precision agriculture”, Computers and
Electronics in Agriculture, Vol.60, pp.144-155. Tisa, T.A., Nisha, Z.A., and Kiber, M.A. (2013), “Design of an
enhanced temperature control system for neonatal incubator”, Bangladesh Journal of Medical Physics, Vol.5, No.1, pp.53-61.
Verdouw, C.N., and Beulens, A.J.M. (2013), “Virtualisation of floricultural supply chains: A review from an internet of things perspective”, Computers and Electronics in Agriculture, Vol.99, pp.160-175.
Vreman, H.J. (2004), ‘Phototherapy: Current methods and future directions’, Seminars Perinatology, Vol.28, pp.326-333.
Wang, X. (2011), “Application research of ecological environment monitoring based on internet of things technology”, Transducer
and Microsystems Technologies, Vol.30, pp.149 -152. WHO (2018), ‘Preterm Birth’, World Health Organization
Available from: https://www.who.int. [Last accessed on July 20, 2019].
Woodgate, P., and Jardine, L.A. (2011), “Neonatal Jaundice”, BMJ
Clinical Evidence, 0319.
Authors’ Biographical Notes:
Solomon C. Nwaneri is a Lecturer at the Department of
Biomedical Engineering, University of Lagos Nigeria. He obtained
his B. Eng. degree in Electrical/Electronic Engineering from the
Federal University of Technology Owerri (FUTO) Nigeria in 2001
and a Master’s degree in Project Management Technology from
the same University in 2009. He also obtained another Master’s
degree in Electrical/Electronic Engineering (Electronic option)
from the University of Lagos Nigeria in 2014 and a PhD in
Industrial/Production Engineering in 2017 from the University of
Ibadan, Nigeria. His Research interests are in Biomedical
Instrumentation, Healthcare Optimization and Analytics.
Jesubori W. Sojobi is a Lecturer at the Department of
Mechanical and Biomedical Engineering, Bells University of
Technology, Ota, Nigeria. She obtained her B.Eng degree in
Biomedical Engineering from Bells University of Technology, Ota,
Nigeria in 2016 and a Master’s degree in the University of Lagos,
Nigeria in 2019. Her research interests are in Bioinstrumentation
and tissue engineering. B.Sc. degree in Electronic/Computer
Engineering from the Lagos State University Nigeria in 2003 and a
Master’s degree in Biomedical Engineering from the University Of
Lagos Nigeria in 2019. Her research interests are in Telemedicine
and biomaterial.
Aderounwi O. Oyelade is an entrepreneur. She obtained her
B.Sc. degree in Electronic/Computer Engineering from the Lagos
State University Nigeria in 2003 and a Master’s degree in
Biomedical Engineering from the University of Lagos Nigeria in
2019. Her research interests are in Telemedicine and biomaterials.
Beatrice N. Ezenwa is a consultant paediatrician working with
Lagos University Teaching Hospital Lagos, Nigeria, and a
Lecturer in the Department of Paediatrics of the College of
Medicine, University of Lagos. She obtained her MBBS degree
from the University of Ilorin, Kwara state in Nigeria in 2000 and a
Master’s degree in Public Health (MPH) IN 2012 from the
University of Lagos, Nigeria. She also obtained her postgraduate
fellowship (FMCPaed) from the National Postgraduate Medical
College of Nigeria/ Lagos University Teaching Hospital in 2012.
Oluwaseyi J. Balogun is a lecturer in the Department of
Biomedical Engineering University of Lagos, Nigeria. He obtained
both B.Sc. and M.Sc. (Hons) in Systems Engineering from
University of Lagos in year 2008 and 2014 respectively. His
research interests include Medical Device, Neuroengineering,
Robotics, Renewable energy and Stochastic Process.
Ugochi C. Uregbulam is a lecturer in the Department of
Biomedical Engineering, University of Lagos, Nigeria. She
obtained her B.Sc. degree in Mechanical Engineering from the
University of Lagos, Nigeria in 2008 and a Master’s degree in
Mechanical Engineering (Thermofluids option) from the same
University in 2012. She is currently doing her PhD degree in
Mechanical Engineering with a research focus on Medical devices
for Neonates. Her research interests are in the modelling and
design of biomedical devices and fluid mechanics.
K.S. Banerjee and S. Kassie: Testing of Physical-Mechanical Properties of Blue Limestone Used in Pavements in Trinidad and Tobago: A Preliminary
Study 21
Testing of Physical-Mechanical Properties of Blue Limestone Used in
Pavements in Trinidad and Tobago: A Preliminary Study
Kailas S. Banerjee a,Ψ, and Shane Kassie b
Department of Civil and Environmental Engineering, The University of the West Indies, St. Augustine Campus, Trinidad and Tobago, West Indies.
(Received 17 February 2020; Revised 06 July 2020; Accepted 17 July 2020)
Abstract: Aggregates used in pavement construction need greater strength to withstand the load of crushing,
degradation and disintegration. It is of high importance to analyse the toughness and abrasion resistance of the
aggregate prior to its usage. In Trinidad and Tobago, blue limestone is mainly used as source for these aggregates.
This blue limestone has two varieties, namely layered limestone and massive limestone. The layered variety contains
soft mica rich layers, which are sandwiched between hard calcite rich layers. Micro-structure (fabric) and other
geological features play important role in defining the resistance and abrasion resistance of these aggregates. In
present study, it was found that aggregate crushing and aggregate impact values were nearly two times lower in the
massive limestone than the layered limestone. Whereas, the loads required for the 10% fines were more than two times
lower in the layered limestone than the massive quality. However, it was found that the specific gravity values were
different in layered and massive limestones (2.3 and 2.5 respectively). Moreover, these measured mechanical
properties were combined into a single characteristic, Toughness Index (TI), as performance indicator of overall
quality of aggregates. The TI values also suggested that the layered limestones were weaker than the massive
limestone. The layered limestones did not satisfy the needs to be aggregates of international quality for pavement
construction. However, the massive limestones were found suitable for this purpose.
Keywords: Aggregates, pavement construction, mechanical properties, toughness index
1. Introduction
Aggregate, which is the physical framework material for pavement and road construction (Hill et al., 2001; Kamal et al., 2006; Mohajerani et al., 2017 amongst others), can contain a crushed stone content in excess of 50% of the coarse aggregate particles (FHWA, 1993). It is important to note that these granular aggregates are subjected to significant amount of wear and tear through the span of their service life. Therefore, aggregates with low resistance to abrasion should be avoided for construction of pavements (Wu et al., 2001; Ozcelik, 2011). It is also well-known that different asphalt-mix strength can be expected from different types of aggregates with different petrology, strength and grain shape (Hill et al., 2001; FHWA, 1993). As a result, the quality of aggregates (especially long-term durability, aggregate impact value and crushing value) can determine the mechanical properties of asphalt-mix (Kamal et al., 2006; Kahraman and Toraman, 2008; Ugur et al., 2010; Mohajerani et al., 2017). These geological properties are widely recognised and accepted to have strong control due to their contrasting mineral assemblage and different characteristics (e.g., shape, orientation and arrangement of grains) (Tuğrul and Zarif, 1999; Tandon and Gupta, 2013, Banerjee and Melville, 2015).
Globally numerous studies have been conducted on the influence of these geological properties in aggregates (Tuğrul and Zarif, 1999; Tandon and Gupta, 2013, Banerjee and Melville, 2015). Searches conducted so far have found negligible amount of available research on these controlling factors in the aggregates used in Trinidad and Tobago road and pavement industry. In Trinidad and Tobago, blue limestone is one of the major type of aggregate used in this sector (Lalla and Mwasha, 2014). In a previous study, one of the present author has indicated a strong control of some of the geological properties on the aggregates commonly used in Trinidad and Tobago construction sector (Banerjee and Melville, 2015). Present study is designed to investigate the suitability of aggregates commonly used for pavement construction in Trinidad and Tobago, and to other regions, where these aggregates are being exported. To establish the suitability, the aggregates were examined particularly to satisfy their resistance to abrasion produced by static, dynamic, permanent and cyclic loads.
Therefore, the objectives of the present study are to: (a) examine some important mechanical properties of the blue limestone, (b) calculate the Toughness Index (TI) of these aggregates and (c) finally to provide information
ISSN 0511-5728 The West Indian Journal of Engineering
Vol.43, No.1, July 2020, pp.21-25
K.S. Banerjee and S. Kassie: Testing of Physical-Mechanical Properties of Blue Limestone Used in Pavements in Trinidad and Tobago: A Preliminary
Study
22
on suitability of the blue limestone in local road and transportation sector.
2. Methodology
2.1 Sample Collection
Northern Range blue limestones have two verities, massive limestone and layered limestone. Present study was carried out on both types of metamorphosed blue limestone samples, collected from the Northern Range of Trinidad. A total of 30 fresh rock samples (15 from each verities) were collected from a local quarry in La Pastore district along Cutucupano (i.e., 10°43’15.15” N and 61°28’41.40”W).
2.2 Mechanical Analysis of Aggregates
Quality assessment of rock samples for the suitability to be used as aggregates for pavement construction was done by examining some important and relevant mechanical properties. These properties include porosity, specific gravity (SG), Los Angeles Abrasion (LAV), Aggregate Impact Value (AIV), Aggregate Crushing Value (ACV), and the 10% Fines Value (TFV). All these properties were tested in the Department of Civil and Environmental Engineering, University of West Indies, St. Augustine Campus, Trinidad and Tobago. Porosity and SG were measured following ASTM standard (ASTM, 2014). LAV, AIV, ACV and TFV tests were performed according to the standards of ASTM C131 (ASTM, 2003), BS: 812-110 (BSI, 1990a) and BS: 812-111 (BSI, 1990b) and BS: 812-112 (BSI, 1990c), respectively. Aggregates for this test were crushed into 1 inch to 3/8 inch fractions before LAV tests were performed, while aggregate fractions above 3/8 inch size were selected for AIV and ACV tests. Aggregates, which pass through a 2.36 mm sieve are defined as fine aggregates, and in TFV test the aim is to determine the load required to produce 10% of the fine fraction of the aggregate. Each value was obtained by averaging vigilant test results from individual sample in order to minimise possible experimental errors particularly in volume measurement (ISRM, 1981; Banerjee and Melville, 2015).
2.3 Toughness Index of aggregates
For a better representation of these mechanical properties of the aggregates, Kamal et al. (2006) have developed a classification of aggregates on the basis of a mechanical index, which is unified from measured LA, AI, AC, TF and SG values (see Table 1).
Table 1. Range of TI for Aggregates Specification
TI range Rating Use >97 Very good Road Surfacing and Base 95–97 Good Base and Subbase 90–95 Fair Subbase only <90 Poor Use with caution
Source: Based on Kamal et al. (2006)
This index has been termed as Toughness Index by these researchers. They also indicated that this index would not preclude the importance of initial testing, rather it could represent a unified, weighted and comprehensive value or index for any routine quality control or assessment of the source materials.
In this study, TI was calculated using the following equation (after Kamal et al., 2006):
(1)
Where,
3. Results
The results obtained from the selected analyses of both the verities of limestones are summarised in Table 2. This table also provides the range of values for each test conducted and the international standard values for these tests. Samples from the layered limestone showed higher porosity values (with the average of 2.18%) than the massive varieties (with the average porosity of 0.44%). The specific gravity values were also found different for both layered and massive limestones, with the average values of 2.3 and 2.5, respectively.
LA values obtained from the layered limestone samples were higher (with average of 42.3 ± 2.6%) than the LA values observed in the massive limestones (with average of 34.8 ± 2.3%). AIV and ACV test results also showed similar trends, with higher values in the layered limestones (with average of values of 50.0 ± 2.8% and 46.4 ± 2.5%, respectively) than those of the massive varieties (with average of values of 23.2 ± 2.1% and 28.2 ± 2.0 %, respectively). The loads required to produce 10% fines from the aggregates were higher in the massive limestones (with the average load of 93.7 ± 5.1 kN) than the layered varieties (with the average load of 38.0 ± 2.8 kN).
Based on Equation (1), TI values for each aggregate samples in the present study have been calculated and are presented in Table 2. The layered limestone samples showed lowered TI values (with average of values of 74.7) than the TI values calculated for the massive limestones (with average of values of 92.6).
K.S. Banerjee and S. Kassie: Testing of Physical-Mechanical Properties of Blue Limestone Used in Pavements in Trinidad and Tobago: A Preliminary
Study
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Table 2. LA, AIV, ACV, Load to TFV, SG and TI of Analysed Blue Limestone
Range of values for each of the test: 32.8 to 36.4 19.6 to 26.8 24.8 to 30.2 85.6 to 98.5 2.2 to 2.8 -
International standards: 19-30* < 30** < 35** > 50***
* LA values for limestone (Mohajerani et al., 2017) ** European Standards for Aggregates (Mitchel, 2015) *** Specification for Highway Works, Clause 803 (HMSO, 1986)
4. Discussion
The two varieties of limestones selected in this present study showed a strong difference in their mechanical properties. It is important to note that lower values for LA, AIV and ACV are required in a standard pavement aggregate, while higher values are required in case of TFV. LAV is a standard method to determine the abrasion resistance of any aggregate (Kahraman et al., 2010; Mohajerani et al., 2017). In this present study, LA values were higher in the layered limestones than the other variety (nearly 1.2 times). This indicates that the layered limestones can break easily upon impact and degradation, which occur during handling, batching and lay-down operations in pavement construction (Meininger, 2004; Mohajerani et al., 2017).
The average values found in both layered and massive limestones were higher than the internationally recommended LA values (with the range value of 19-30%, Mohajerani et al., 2017). However, in the massive variety these values (with the average value of 34.8%) were closer to the indicated international range than that
of the layered counterpart (with the average value of 42.3%). AIV represents the aggregate toughness to resist fragmentation (Mildard, 1993; Stalheim, 2014). Present study found that the aggregate impact values were more than 2 times higher in the layered limestone than the massive limestones. This indicates that massive variety of limestone is more suitable for pavement construction, while the layered limestone, with the AI values of 50%, may be of poor technical values and therefore, may be non-desirable for pavement construction (Mildard, 1993; Stalheim, 2014).
According to the European Standards, an AIV with less than 30% value is usually required for pavement aggregates (Mitchel, 2015). In present study, this was achieved only by the massive limestones. The aggregate crushing values correspond to the aggregate resistance to crushing under compression applied by gradual loading (Mildard, 1993; Stalheim, 2014). This work showed that the layered limestones had nearly two times higher AC values than the massive variety. This indicates that the massive limestone is more resistant to compression and
K.S. Banerjee and S. Kassie: Testing of Physical-Mechanical Properties of Blue Limestone Used in Pavements in Trinidad and Tobago: A Preliminary
Study
24
thus, can be a higher quality pavement aggregate (Mildard, 1993; Stalheim, 2014).
Similar to AIV, the massive limestone samples had only satisfied the need of the European Standards ACV criteria (less than 35%; Mitchell, 2015). TFV test determines the load required to produce 10% fines from the aggregates (Kamal et al., 2006). In this study, it was observed that the layered limestones needed less than 40 kN load, which is lower than the typical USA and UK specifications (i.e., load should be more than 50 kN) (HMSO, 1986). However, TFV in the massive limestones were found within the permissible range specified in the USA and UK standards of 50-110 kN loads (HMSO, 1986).
Toughness index, which is a unique value, can be used as performance indicator for the aggregates (Kamal et al., 2006). According to this classification (see Table 1), aggregates with the TI values less than 90 can be considered as of poor quality and therefore, can be either avoided or to be used with proper caution. In this study, the layered limestones showed the TI values below 90. They would be inferred as of poor quality and should be used with proper preventive measure. However, it was found that these values in the massive limestones were fair in their quality and would be suitable for pavement construction purposes.
Because of the presence of soft mica rich layers, these variations observed in the selected aggregate samples are expected. These mica rich layers are sandwiched between calcite rich layers (see Figure 1).
Figure 1. Photomicrograph of Layered Limestone
Presence of these layers indicates impurities in the
compactness of the aggregates (Tuğrul and Zarif, 1999; Tandon and Gupta, 2013, Banerjee and Melville, 2015). These impurities are to be correlated with comparatively high porosity values of the layered limestone to its lower relative density. It is important to note that the thickness of the soft layers varies from the scale of meter to micron (see Figures 2 and 3).
Figure 2. Massive blue limestone samples collected from local quarry in La Pastore district along Cutucupano
Figure 3. Layered blue limestone samples collected from local quarry in La Pastore district along Cutucupano
5. Conclusion and Recommendations
Determination of mechanical properties, especially toughness and abrasion resistance of aggregates is very vital in the selection aggregates. Though this study is primitive, it can be very important and informative for Trinidad and Tobago, and for the region. The specific conclusions from this study are as follow:
1) The massive limestone was found to have half aggregate crushing and impact values than that found in the layered limestone.
2) The loads required for 10% fines were more than two times lower in the layered limestone than the massive verity.
3) The TI, which can represent a unified mechanical property to classify aggregates for pavement construction, also suggested layered limestone to be of poor quality.
4) The mechanical properties measured (except LA values) in both types of limestones indicated that the massive limestones met the internationally recognised standards required in desirable road and pavement aggregates. However, the layered limestones were unable to meet the respective international standards.
K.S. Banerjee and S. Kassie: Testing of Physical-Mechanical Properties of Blue Limestone Used in Pavements in Trinidad and Tobago: A Preliminary
Study
25
Detailed petrographic and micro-structural (fabric) analysis will be helpful to assess the control of these micro-fabric on these mechanical properties. Acknowledgements:
The author would like to express his gratitude to the Department of Civil and Environmental Engineering, The University of West Indies, Trinidad and Tobago for the support in carrying out this study
References:
ASTM (2003), ASTM C 131: Abrasion Test, American Society for Testing and Materials, Los Angeles
ASTM (2014), ASTM D854-14: Standard Test Methods for
Specific Gravity of Soil Solids by Water Pycnometer, American Society for Testing and Materials, Los Angeles.
BSI (1990a), BS 812-110:1990: Testing Aggregates. Methods for
Determination of Aggregate Crushing Value, British Standards Institution, London.
BSI (1990b), BS 812-111:1990: Testing Aggregates. Methods for
Determination of Ten Per Cent Fines Value (TFV), British Standards Institution, London
BSI (1990c), BS 812-112:1990: Testing aggregates. Method for
determination of aggregate impact value (AIV), British Standards Institution, London
Banerjee, K.S., and Melville, R. (2015). “Preliminary Investigation of Geotechnical Properties of the Rock Aggregates Commonly Used for Civil Engineering Construction in Trinidad and Tobago”, The West Indian Journal of Engineering, Vol.38, pp.15-20.
FHWA (1993), A Study of the Use of Recycled Paving Material -
Report to Congress, Federal Highway Administration Report FHWA-RD-93-147; 1993.
HMSO (1986), Clause 803: Specification for Highway Works.
Manual for Contract Documents for Highway Works, Her Majesty's Stationery Office, London, UK.
Hill, A.R., Dawson, A.R., and Mundy M. (2001), “Utilisation of aggregate materials in road construction and bulk fill”, Resources, Conservation and Recycling, Vol.32, pp. 305-320.
ISRM (1981), Rock Characterisation, Testing and Monitoring.
ISRM Suggested Methods, International Society for Rock Mechanics/Pergamon Press, Oxford.
Kahraman, S., Fener, M., and Gunaydin, O. (2010), “Estimating the abrasion resistance of rock aaggregates from the P-wave velocity”, Proceedings of the 1st International Applied
Geological Congress, Department of Geology, Mashad, Iran, http://conference.khuisf.ac.ir/DorsaPax/userfiles/file/pazhohesh/zamin%20mashad/92.pdf . Accessed on 06 July, 2020
Kahraman, S., and Toraman, O.Y. (2008), “Predicting Los Angeles abrasion loss of rock aggregates from crushability index”, Bulletin of Materials Science, Vol.31, pp.173-177. doi:10.1007/s12034-008-0030-4
Kamal, M.A., Sulehri, M.A. and Hughes, D.A.B. (2006), “Engineering characteristics of road aggregates from northern Pakistan and the development of a toughness index”, Geotechnical and Geological Engineering, Vol.24, pp. 819–831. https://doi/10.1007/s10706-005-6610-9
Lalla, J.R.F., and Mwasha, A. (2014), “Investigating the compressive strengths of guanapo recycled aggregate concrete as compared to that of its waste material”, The West Indian Journal
of Engineering, Vol.36, pp.12-19. Meininger, R., (2004), “Micro-deval vs. L.A. abrasion”, Rock
Products, Vol.107, pp. 33-35. Millard, R.S. (1993), Road Building in the Tropics. Transport
Research Laboratory, State of the Art Review 9. H.M. Stationery Office, London.
Mitchell, C. (2015). “Construction aggregates: evaluation and specification”, In: The Third International Forum for Industrial
Rocks and Mining, Fujairah, United Arab Emirates, 30 March - 1 April 2015 (http://nora.nerc.ac.uk/id/eprint/510909/1/Construction%20aggregates%20evaluation%20and%20specification.pdf accessed on 03 May 2020)
Mohajerani, A., Nguyen, B.T., Tanriverdi, Y., and Chandrawanka, K. (2017), “A new practical method for determining the LA abrasion value for aggregates”, Soils and Foundations, Vol.57, pp. 840-848. https://doi.org/10.1016/j.sandf.2017.08.013
Ozcelik Y. (2011), “Predicting Los Angeles abrasion of rocks from some physical and mechanical properties”, Scientific Research
and Essays, Vol.6, pp.1612-1619. Stålheim, J. (2014), Comparative Study of Established Test
Methods for Aggregate Strength and Durability of Archean
Rocks from Botswana, M.Sc. Thesis. Uppsala University UPTEC W13044 ISSN 1401-5765. Published digitally at the Department of Earth Sciences, Uppsala University, 2014 (http://www.w-program.nu/filer/exjobb/Jessica_Stalheim.pdf accessed on 15 December, 2019)
Tandon, R.S., and Gupta V. (2013), “The control of mineral constituents and textural characteristics on the petrophysical and mechanical (PM) properties of different rocks of the Himalaya”, Engineering Geology, Vol.153, pp. 125-143.
Tuğrul, A., and Zarif, I.H. (1999), “Correlation of mineralogical and textural characteristics with engineering properties of selected granitic rocks from Turkey”, Engineering Geology, Vol.51, pp.303-317.
Ugur, I., Demirdag, S., and Yavuz, H. (2010), “Effect of rock properties on the Los Angeles abrasion and impact test characteristics of the aggregates”, Materials Characterisation, Vol.61, pp.90-96.
Wu, R.K., Chen, B., Yao, W., and Zhang, D. (2001), “Effect of coarse aggregate type on mechanical properties of high-performance concrete”, Cement and Concrete Research, Vol.31, pp.1421-1425.
Authors’ Biographical Notes:
Kailas Sekhar Banerjee is a Lecturer in Geology, in the
Department of Civil and Environmental Engineering at The
University of the West Indies since 2012. His academic and
research interests are Engineering Geology, Environmental
Geology, Environmental Radiation, Waste Management and
Hydrogeology.
Shane Kassie is an alumni of the Department of Civil and
Environmental Engineering at The University of the West Indies.
He completed his degree in Civil Engineering in the year 2019-
2020.
O.A.A. Eletta et al.: Adsorption of Pb(II) and Phenol from Wastewater Using Silver Nitrate Modified Activated Carbon from Groundnut (Arachis
hypogaea L.) Shells 26
Adsorption of Pb(II) and Phenol from Wastewater Using Silver Nitrate Modified Activated Carbon from Groundnut (Arachis hypogaea L.) Shells
Omodele A. A. Eletta a, Ibrahim O. Tijani b, and Joshua O. Ighalo c,Ψ
Department of Chemical Engineering, Faculty of Engineering and Technology, University of Ilorin, Ilorin, P. M. B. 1515, Nigeria.
1. Introduction Pharmaceutical industry wastewater has been shown to contain a plethora of pollutants including lead and phenol (Araujo et al., 2018; Olarinmoye et al., 2016; Snyder et al., 2010). In a bid to achieve environmental sustainability, much research effort has been invested in the mitigation of these pollutants from the ecosystem (Adeniyi and Ighalo, 2019; Rani and Sud, 2015). Lead is a very toxic element, even at low concentrations. It affects the central nervous system, kidneys, liver, and gastrointestinal system, and it may directly or indirectly cause diseases such as anaemia, encephalopathy, hepatitis, and the nephritic syndrome (Wang et al., 2010). According to the USEPA, the permissible level for lead in drinking water is 0.05 mg/l (Sarkar et al., 2003).
Phenol is an organic pollutant that has potential toxicity to human health. Phenol can be found in wastewater from different chemical industries including pulp and paper, petroleum refinery, dye synthesis, coal gasification and pharmaceutical industries. Therefore, effective removal of phenol from the wastewater and reducing its concentrations to the permitted levels before discharging are challenging issues. The US Environmental Protection Agency (USEPA) regulations suggest phenol concentration below 1 ppm for wastewater (Abussaud et al., 2015). Adsorption is one of the most attractive approaches for heavy metals and
phenolic compounds removal due to its high efficiency, simple and safe treating processes, versatility for different water systems and low cost.
Many adsorbents, including active carbons, chitosan, resins, and carbon nanotubes have been used for removal of heavy metals or/and phenolic compounds (Ighalo and Adeniyi, 2020a; Ighalo and Adeniyi, 2020c). However, there are some defects, such as low efficiency, bad stability and difficult separation, limiting their practical application (Yang et al., 2015). The mitigation of lead has been investigated in recent times using Terminalia
catappa seed husk biochar (Canlas et al., 2019), live and dead cell mass of Pseudomonas aeruginosa (Ighalo and Adeniyi 2020d; Karimpour et al. 2018), organic acid modified rubber leaf powder (Fadzil et al., 2016), Sago bark (Metroxylon sago) powder (Fauzia et al. 2018), cacao pod (Theobroma cacao) rind waste (Eletta et al., 2020; Moelyaningrum, 2018), fish scales (Eletta and Ighalo, 2019; Ighalo and Eletta, 2020) and a host of others (Eletta et al., 2019). The mitigation of phenol has been investigated in recent times using steam activated biomass soot and tire carbon black (Trubetskaya et al., 2019), activated carbon from black wattle bark waste (Lütke et al., 2019), spent black tea leaves (Ali et al., 2018) and a host of others. There are no studies reporting groundnut shell used in this domain.
Groundnut (Arachis hypogaea L.) is one of the world’s most popular oilseed crops which is grown as an
ISSN 0511-5728The West Indian Journal of Engineering
Vol.43, No.1, July 2020, pp.26-35
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annual plant, but perennial growth is possible in climates which are warm until harvest. Its high content of oil and protein makes it an important commodity for both human use and livestock feed (Farag and Zahran, 2014). Groundnut shell is of low ash content, low apparent density, and a high degree of porosity which is assured as a good precursor to synthesis activated carbon (Babarinde and Onyiaocha, 2016). Thus, the conversion processing of groundnut shell for activated carbon could ease and reduce the environmental pollution of groundnut shell while making readily available, activated carbon at a reduced cost.
In this study, pharmaceutical wastewater was characterised to determine the level of pollutants present and what chemical species constitute an environmental problem in Ilorin, Nigeria. Phosphoric acid was used to produce activated carbon from groundnut shell at 500˚C and the activated carbon produced was further modified with silver nitrate. After comprehensive characterisation of its physiochemical properties, both adsorbents were applied to remove Pb(II) and phenol from wastewater respectively. The effect of contact time, dosage and temperature on the adsorption of Pb(II) and phenol from wastewater were determined. The adsorption isotherms, kinetics and thermodynamics were also investigated to analyse the adsorption mechanisms. 2. Methodology 2.1 Materials and Equipment The reagents used for this study include: phosphoric acid (H3PO4), silver nitrate (AgNO3), distilled water, phenol (C6H5OH), lead nitrate Pb(NO3)2 and all the chemicals used in this research were of analytical grade. The instruments used are, magnetic stirrer, ball mill, Scanning Electron Microscope (SEM) (Phenom prox, Netherlands), X-ray diffractometer (Bruker D2, Germany), Fourier Transform Infrared spectrophotometer (FTIR) (Nicoletin 10 MX), Branueur-Emmet-Teller analysis (BET) (Quantachrome FS240 NOVA 4200e), Muffle furnace (Sheffield LF4), EDX (JSM-6510LV, England), pH meter, Atomic Absorption Spectrophotometer (AAS) (GBC-902, Australia) and UV spectrophotometer (Model AA-680), respectively. 2.2 Analysis of Wastewater and Preparation of
Simulated Water The wastewater was sourced and analysed to establish pollutant(s) of interest before the synthesis of wastewater in the laboratory. The wastewater was sourced from a pharmaceutical company located at 8o 28’ N, 4o 33’ E in Ilorin, Nigeria. Five (5) litres of the liquid were collected.
The wastewater from the pharmaceutical industry was analysed using Atomic Absorption spectrophotometer (AAS) and UV spectrophotometer to determine the concentration of Pb(II) and phenol, respectively. For the stock solutions of simulated water, 1000 mg/L of Pb(II) and phenol was prepared by
dissolving 1.6 g of lead nitrate and 1.0 g of phenol in 1000 mL deionised water. The stock solution was diluted with deionised water to the desired Pb(II) and phenol concentrations. After adsorption, the supernatant liquids were filtered with Whatmann filter paper.
2.3 Preparation of Adsorbents Groundnut (Arachis hypogaea L.) shell was obtained from a local market and cleaned, sun-dried and further oven-dried at 80⁰C until a constant weight is observed. Thereafter, size reduction was carried out using a ball mill followed by sieving and storage in a desiccator. 50 g each of the precursor was weighed into different beakers and the phosphoric acid solution was added to the precursor in 250 ml beakers based on the impregnation ratio of 1:2. The mixture was stirred continuously using a magnetic stirrer at room temperature for 5 hours thereafter, the mixture was stored for 24 hours (Yakout and El-Deen, 2016). The mixture was filtered and dried in an oven at 110˚C for 24 hours. The dried sample was carbonized directly in a furnace at 500 ˚C in an inert environment.
The activated carbon produced was screened to 100 µm micrometres and washed with 0.5 M phosphoric acid followed by distilled water at room temperature until the washing solution becomes neutral at pH 7. The activated carbon produced was dried in an oven at 110˚C for 6 hours and cooled to room temperature to obtain the H3PO4 activated carbon. Following the procedure described by Amuda et al. (2007), the activated carbon was modified by soaking in a freshly prepared silver nitrate solution (0.5 mg/l). 10 ml of the silver nitrate solution was mixed with 0.5 g of activated carbon in a conical flask, which is according to the method used by Olajire et al. (2016). Thorough mixing was carried out using a magnetic stirrer at 200 rpm to ensure thorough mixing. After the deposition of AgNO3 onto the activated carbon, the silver nitrate modified activated carbon was filtered and dried in an oven at 110°C till dryness was observed. The adsorbent is referred to as modified ground-nut shell activated carbon (MGSAC) whilst the unmodified version was referred to as GSAC. The modification by silver nitrate was done to improve the surface functional groups, increase in adsorbate affinity for the adsorbent and impact a secondary anti-microbial property on the adsorbent.
2.4 Characterisation of the Activated Carbon The groundnut shell activated carbon and silver nitrate modified activated carbon was characterised using FTIR (Nicoletin 10MX) to determine the functional groups responsible for the adsorption. The surface area was determined using Branueur-Emmett-Teller (BET) (Quantachrome FS240 NOVA 4200e) (Adeniyi et al., 2020), the elemental characteristics were obtained by EDX (JSM-6510LV, England).
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2.5 Batch Adsorption Experiment Batch adsorption studies were carried out on both the GSAC and MGSAC to evaluate their adsorption performances. The adsorption was performed by adding 0.1 g of activated carbon into 100 ml of synthesised wastewater in 250 ml conical flask, covered and agitated at 200 rpm using a mechanical shaker for 180 mins to ensure equilibrium at room temperature and pH 7.0 (Amuda et al., 2007). After this, the content was centrifuged at 500 rpm for 20 mins. The resulting solution was decanted into brownish bottles and stored for analysis. Whatman filter paper was used to filter the content and it was analysed using UV- Spectrophotometer for the residual concentration at 270 nm wavelength for phenol and Atomic Absorption Spectrophotometer for Pb (II). The adsorption capacity, (qe) (mg/g) was evaluated by using Equation (1).
(qe) (mg/g) = [(Co - Ce)/v ] / M (1)
Where Co (mg/L) is the initial concentration of Pb(II) and phenol in contact with adsorbent, Ce (mg/g) is the final concentration of Pb(II) and phenol after the batch adsorption procedure at time t, m (g) is the mass of adsorbent and V is the volume of the adsorbate in litres (L). The percentage of removal was evaluated using Equation (2)
Removal (%) = (Co and Ce) / Co (2)
Where Co and Ce are the Pb(II) and Phenol concentration at initial state and equilibrium respectively. 2.6 Parametric Studies The effect of contact time on adsorption was studied by setting up nine conical flasks on a mechanical shaker having 0.1 g of MGSAC separately, and GSAC in 100 ml of Pb(II) and phenol solutions of 25 mg/l, 50 mg/L, 75 mg/l, 100 mg/l, and 125 mg/l respectively, and agitated at 200 rpm at room temperature. The beakers were removed after contact times ranging from 10 to 180 minutes. The effect of adsorbent dose on the adsorption of Pb(II) and phenol was studied by varying the activated carbon dose between 0.2-1.0 g in nine conical flasks having 100 ml of 100 mg/l concentration of Pb(II) and phenol respectively (Gupta and Rafe, 2013). Each was then agitated at 200 rpm for 3 hours at room temperature. The effect of temperature was studied at intervals of 35˚C, 45˚C, and 55˚C. 3. Results and Discussion 3.1 Characterisation of Pharmaceutical Effluent The produced wastewater from the pharmaceutical industry was analysed using AAS and UV spectrophotometer to measure the concentration of Pb(II) and phenol respectively. The results gotten show that the concentration of Pb(II) and phenol are 0.2 ppm and 3.7 ppm respectively which are above the maximum permissible limits by WHO (see Table 1). The maximum
permissible limits of lead in different categories of water as proposed by different organisations standard are shown in Table 1. Phenol and phenolic compounds have been listed by several regulatory bodies on the priority pollutants list and have proposed the maximum permissible limits of phenol in different categories of water (see Table 2) (Sonawane and Korake, 2016).
Table 1. Maximum Permissible limit of Lead in Water Standard Type Amount (mg/L) WHO Drinking water 0.01 USEPA Wastewater 0.05
Table 2. Maximum Permissible limit of Phenol in Water
Agency Type of water Maximum permissible limit USEPA Wastewater 1.00 ppm WHO Drinking water 0.1 ppm
3.2 FTIR Spectra for the Adsorbent The presence of various functional groups on the surface of the adsorbent was analysed with Thermo-Fisher FT-IR analyser (Scientific, Nicolet 5700) within the spectrum range of 400–4000 cm−1. The presence of these functional groups on the activated carbon was responsible for adsorption of different heavy metal from aqueous solution (Rai et al., 2015). The FTIR of the GSAC and the MGSAC are shown in Table 3.
Table 3. The FTIR of the GSAC and the MGSAC and BET Analysis
The IR peak observed in the MGSAC and GSAC ranged from 58.89-3772.1 cm-1 and 23.706 cm-1 and 3857.8 cm-1 respectively. The peak height ranged from 38.2-39.8 cm-1 and 14.3-17.8 cm-1 for both MGSAC and GSAC respectively. Changes were observed in the functional groups of both adsorbents. There was the appearance of the -C≡C- at peak of 2191.4 cm-1 after the modification of activated carbon. The images of both MGSAC and GSAC are shown in Figures 1 and 2, respectively.
The FTIR showed appearance, disappearance or broadening of the peaks after the carbonisation and impregnation with both phosphoric acid and silver nitrate (Olajire et al., 2016). There were changes in the functional groups of both samples and upon surface modification, there are appearances of some additional peaks at MGSAC that can be attributed to stretching vibration of OH.
O.A.A. Eletta et al.: Adsorption of Pb(II) and Phenol from Wastewater Using Silver Nitrate Modified Activated Carbon from Groundnut (Arachis
Adsorbent The surface area was determined using Branueur-Emmett-Teller (BET) (Quantachrome FS240 NOVA 4200e). The results of the BET of both GSAC and MGSAC are shown in Table 3. The porosity of MGSAC was well developed albeit with lower surface area, microspore volume, and larger average pore diameter. The pore diameter of 3 nm and 2 nm for GSAC and MGSAC shows that the adsorbents are mesoporous. The range for mesoporous adsorbents is between 2 and 50 nm. The BET results also show that the unmodified adsorbent has a higher surface area than the modified one. The modification reduced the surface areas by over two times. This is because some of the pores of the adsorbent are occupied by the silver nitrate. However, another performance advantage is gotten from the utilisation of silver nitrate such as modification of surface functional groups, an increase in adsorbate affinity and the presence of a secondary anti-microbial ability of the adsorbent. 3.4 SEM-EDX for the Adsorbent Figure 3 is the SEM image of GSAC and Figure 4 is the SEM image of MGSAC. These images were used to verify the possible changes in morphological features of the samples before and after the modification. As shown in Figure 3, the surface of the GSAC is irregular and relatively rough with a dense fibrous structure. This
suggests the possibility of a high surface area for adsorption (Ighalo and Adeniyi, 2020b). After the modification with silver nitrate, Figure 4 shows that the surface of the MGSAC was regular and has more complex pore structures compared to the GSAC. These results indicated that the physical characteristics of GSAC that was modified with silver nitrate were improved. Also, it improved the accessibility of active sites and the adsorption of Pb(II) and phenol during the adsorption process. From the EDX analysis of the MGSAC (see Table 4), it was observed that the analysis of the EDX revealed the presence of C, O, Si, and P. The higher peak of carbon (C) in Table 4 was attributed to the effect of carbonisation of the groundnut shell at high temperature.
Table 4. Composition of the Elements in MGSAC Element Number
Element Symbol
Element name
Atomic Conc.
Weight Conc.
6 C Carbon 74.80 66.64 8 O Oxygen 18.59 22.09 15 P Phosphorus 2.15 4.94 14 Si Silicon 1.23 2.56 7 N Nitrogen 2.34 2.43 9 F Fluorine 0.79 1.11 16 S Sulfur 0.07 0.16 17 Cl Chlorine 0.04 0.11
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3.5 Parametric Studies 3.5.1 Effect of Contact Time
The effect of contact time on adsorption of Pb(II) and phenol onto prepared GSAC and MGSAC are shown in Figures 5-8. These were conducted at 25 mg/L initial concentration, 25˚C, 200 rpm shaking speed and 0.2 g adsorbent in 100 ml aqueous solution. The result revealed that the uptake of adsorbate increased at the initial stage of the contact time for all the concentrations (Ighalo et al., 2020a; Mall et al., 2006). This is because, at the beginning of the adsorption process, all the active sites on the adsorbent are vacant. Hence, adsorption proceeds at a faster rate and desorption at a lower rate as the active sites get occupied (Ighalo et al., 2020b; Rashid et al., 2016). For an initial concentration of 25 mg/L, the adsorption capacity and percentage removal of the MGSAC were higher compared to the GSAC as shown in Figures 6-9. This is the same for all other domain of initial concentrations. It was also discovered that the percentage removal of Pb(II) and phenol also increased with increasing time. This is because more pollutant molecules move through the solid-liquid film with time onto the adsorption sites. At equilibrium virtually, all pores are filled hence there is no significant uptake of the pollutant species anymore.
Figure 5. Effect of Contact Time on Adsorption of Pb(II) (at 25 mg/L initial concentration)
Figure 6. Effect of Contact Time on Adsorption of Phenol (at 25 mg/L initial concentration)
Figure 7. Effect of Contact Time on Percentage Removal of Pb(II)
(at 25 mg/L initial concentration)
Figure 8. Effect of Time on Percentage Removal of Phenol (at 25
mg/L initial concentration)
The rapid uptake at the commencement of adsorption is due to a very high mass transfer driving force which reduces as the concentration of the pollutants in the solutions drops. The drop in 2% removal for MGSAC from 90 minutes to 120 minutes and then increase at 150 minutes was observed in Figure 7. This was only a slight drop and could be due to experimental error.
3.5.2 Effect of Adsorbent Dosage
The adsorption dosage varied from 0.2-1.0 g and the effect of each on adsorption capacity and removal efficiencies of Pb(II) and phenol are shown in Figures 9-12. These were conducted at 25 mg/L initial concentration, 25˚C, 200 rpm shaking speed and 180 minutes contact time. It was observed that the adsorption capacity for both GSAC and MGSAC had increased from 14.92 to 73.59 mg/g and 14.98 to 74.64 mg/g respectively. The removal efficiencies for both GSAC and MGSAC had increased from 94.46 to 98.12% and 99.52 to 99.92%, respectively.
As the adsorbent doses increase, the adsorption capacity and removal efficiency of Pb(II) and phenol
O.A.A. Eletta et al.: Adsorption of Pb(II) and Phenol from Wastewater Using Silver Nitrate Modified Activated Carbon from Groundnut (Arachis
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increase. This can be directly linked to the availability of adsorption sites with an increasing amount of adsorbent (Simha et al., 2016). It was also discovered that the adsorption capacity and removal efficiency of the MGSAC dosage were higher compared to the GSAC. Hence the modification improved the performance of the adsorbent.
Figure 9. Effect of Dosage on Adsorption Capacity of Pb(II)
Figure 10. Effect of Dosage on Removal Efficiency of Pb(II)
Figure 11. Effect of Dosage on Adsorption Capacity of Phenol
Figure 12. Effect of Dosage on Removal Efficiency of Phenol
3.5.3 Effect of Temperature
The effect of temperature and the impact was studied by varying temperature (35˚C, 45˚C, and 55˚C), The impact of the variation on adsorption capacity and removal efficiencies were investigated within the time interval of 15-55 min as shown in the Figure 13. These were conducted at 25 mg/L initial concentration, 200 rpm shaking speed and 0.2 g adsorbent in 100 ml aqueous solution. The MGSAC was observed to have a higher adsorption rate than the GSAC at the three temperatures. It was also observed that, as the temperature increased the adsorption capacity decreased, which means that the adsorption for Pb(II) and phenol with MGSAC are exothermic, and, a lower temperature is favourable for adsorption of phenol (Adeniyi and Ighalo, 2019). However, beyond the optimal threshold, there was no observable change in adsorption capacity with time (x-axis) due to the filled up pore spaces on the adsorbent.
Figure 13. Plot of Qt against Time for Pb(II) at 35˚C, 45˚C,
and 55˚C
3.6 Adsorption Equilibrium Isotherm Three adsorption isotherm equations were used in the investigation of the adsorption experimental study: Langmuir, Freundlich and Temkin models. The
O.A.A. Eletta et al.: Adsorption of Pb(II) and Phenol from Wastewater Using Silver Nitrate Modified Activated Carbon from Groundnut (Arachis
hypogaea L.) Shells
32
application of the three isotherm equations was compared by judging the correlation coefficient, R2 between them. The Lanmuir plot of ce /qe versus qe using the linearised equation was used. It was applied to determine the Langmuir parameters for the adsorption of Pb(II) and phenol unto both GSAC and MGSAC. The Langmuir constants were evaluated from the slope 1/qm and intercept 1/(qmKL) as shown in Tables 5 and 6. The negative values of KL and QL obtained from 25 mg/l to 125 mg/l concentrations for the GSAC indicated the inefficiency of Langmuir model to explain the adsorption process, likewise for the 25 mg/l to 125 mg/l in the MGSAC. But the parameters 1/qm and 1/(qmKL) were positive from 25 mg/l – 125 mg/l for the GSAC, and 25 mg/l - 125 mg/l for the MGSAC.
Table 5. Isotherm Characteristics Parameters of Langmuir, Freundlich and Temkin Isotherm Constants for Pb(II) onto GSAC
can be explained in terms of the separation factor (RL). When 0 < RL < 1, the adsorption process is feasible. The values of RL were less than 1 for both the GSAC and the MGSAC at the same concentrations (which means that they were favourable for the GSAC and MGSAC
adsorption). The closeness of the value of the correlation coefficients (R2) to 1 compared to the Freundlich and Temkin model indicated that Langmuir isotherm is the best-fit isotherm to describe the adsorption of Pb(II) and phenol unto GSAC and MGSAC.
The Freundlich plot of logqe versus logCe was used to determine the Freundlich isotherm parameters for the adsorption of Pb(II) and phenol unto both GSAC and MGSAC. The Freundlich parameters (n and KF) and the correlation coefficients (R2) are shown in Table 5 and 6. The Freundlich exponent, n, for the adsorption of Pb(II) indicated the favorability of the adsorption process. Generally, values of n in the range 2 – 10 represent good, 1 – 2 moderately good, and less than 1 poor adsorption characteristics (Babatunde et al., 2019). It was discovered that the R2 of the MGSAC are higher than the GSAC, indicating higher adsorption capacity for Pb(II) molecules compared to GSAC.
The Temkin plot of qe against lnCe was used to determine the Temkin isotherm parameter for the adsorption of Pb(II) and phenol onto the adsorbent. The linear isotherm constants and coefficients of determination for both the GSAC and the MGSAC are presented in Table 5 and 6. It shows that the equilibrium binding constant (α) (L/mg) which corresponds to the maximum binding energy increased with increase in concentration (Olajire et al., 2016). The constant β which is related to the heat of adsorption equally increased with increase in concentration, but the heat of adsorption of all the molecules in the layer decreased linearly with coverage. The results implied that the affinity of the binding sites for lead and phenol increased with increase in concentration. The correlation coefficient (R2) of the GSAC was higher compared to the MGSAC. However, the low correlation coefficient (R2) of the Temkin model compared to the Freundlich suggested that this model was not more suitable to fit the adsorption of Pb(II) unto activated carbon produced from groundnut shell.
3.7 Kinetics Studies The kinetic data were analysed using both the pseudo-first order and pseudo-second order equations. The pseudo-first order plot of log (qe - qt) versus time gave straight lines with values of K1 and qcal, calculated from the slopes (-k1) and intercepts (lnqe) of the plots respectively. The calculated parameters were presented in Table 7.
The plot of the concentration 25-125 mg/L showed high correlation coefficients for both the GSAC and MGSAC. For the GSAC, the plot of 75 mg/L initial concentration has the highest correlation coefficient of 0.87 while the 100 mg/L has the lowest R2 0.84. However, the MGSAC has the highest R2 of 0.99 at 50 mg/L and the lowest of 0.91.
The values of k and qe for the pseudo-second order model were calculated from the intercepts (1/Ke2) and slope (1/qe) of the plots of t/ qt vs. t, and are presented in
O.A.A. Eletta et al.: Adsorption of Pb(II) and Phenol from Wastewater Using Silver Nitrate Modified Activated Carbon from Groundnut (Arachis
hypogaea L.) Shells
33
Table 8. The closeness of the correlation coefficients (R2) highest values to 1 for both GSAC and MGSAC indicated that the pseudo-second order was fit to describe kinetic data suggesting that, pore diffusion was the rate-limiting step. It can be deduced, that it was best-fit for the MGSAC compare to GSAC.
Table 7. Kinetic Parameters and Correlation Coefficients (R2) Obtained for the First Order Models
3.8 Thermodynamic Studies The standard enthalpy (ΔH°), standard free energy (ΔG°), and standard entropy (ΔS°) are considered to characterise the adsorption process due to the transfer of one mole of solute from the solution onto solid-liquid interface (Olajire et al. 2016). The parameters were determined by the plot of ln Kd against 1/T (Vant Hoff”s plot). The partitioning coefficient Kd (L/mol) of the Pb(II) and phenol towards the activated carbon is an important parameter for examining the Pb(II) and phenol molecule migration through the MGSAC (see Table 9). The values of the ΔG° are negative except at 318 and 328 K at 15 min for the MGSAC. The values of ΔG° for
the adsorption of Pb(II) on MGSAC was higher which indicated that adsorption process was spontaneous and feasible on the MGSAC except for the ones at temperature 318 K and 328 K respectively. The absolute decrease in a negative value of ΔG˚ as the temperature increased indicated that adsorption decreased with rising in temperature. This change in ΔG° value may be due to the increase in the degree of freedom which might enhance desorption rather than adsorption at high temperatures (Rani and Sud, 2015).
Generally, the range of free energy values (ΔG˚) for physio-sorption is between -20 and 0 KJ/mol while chemisorption is between -80 and -400 KJ/mol. The value of the ΔG° fell within the range of 0 to -20 kJ/mol for the adsorption process on MGSAC. The ΔH° values gotten were negative, which varied from -3.3250 kJ/mol to -21.3021 kJ/mol for MGSAC. This showed that the adsorption process of Pb(II) was exothermic (Babarinde and Onyiaocha 2016). It can be seen that the adsorption process on the MGSAC is tending towards chemisorption. The small negative values of ΔS° (-0.0210 to 0.0087 KJ/mol) MGSAC suggested the decreased randomness on solid/solute interface during the adsorption. 4. Conclusion The groundnut shell activated carbon was produced by the impregnation of phosphoric acid in the right proportion and half of the prepared activated carbon was modified with AgNO3 to improve the adsorptive property of the activated carbon. The FTIR was used for suggesting the surface chemistry of the GSAC and MGSAC indicated the large presence of O-H, C=O and N-H. There was the appearance of the -C≡C- after the modification of the activated carbon with AgNO3. FTIR also show the functional molecules (Cellulose, hemicelluloses, lignin and pectin). SEM analysis revealed disordered pores over the carbon particle surface. The EDX analysis confirmed that carbon is the major element. The MGSAC has a higher adsorption capacity and percentage removal compared to the GSAC for all domains of factors.
Table 9. Thermodynamic Parameters for the Adsorption of Pb(II) onto MGSAC Time (min) Temperature (K) Kd ln Kd ΔG (kJ/mol) ΔH (KJ/mol) ΔS (KJ/mol) 15
308 2.5755 0.7246 -1.1239 -20.6215
-0.567 318 0.7286 -0.0831 0.1469
328 0.85 -0.1867 0.5678 25
308 2.5581 0.7119 -1.9578 -12.3254
-0.751 318 1.5035 0.1249 -0.9567
328 1.5493 0.1385 -0.5672 35
308 2.7408 1.7196 -3.4167 -21.3021
-0.0944 318 1.669 0.4568 -1.47I7
328 1.6298 1.3577 -0.8699 45
308 3.6314 2.3447 -8.4325 -3.3250
-0.0087 318 1.8867 4.1695 -9.5794
328 3.2692 2.6787 -3.7686 55
308 17.8333 2.8811 -7.3776 -16.1248
-0.220 318 11.5333 2.4615 -6.3948
328 13.6 2.4314 -7.6199
O.A.A. Eletta et al.: Adsorption of Pb(II) and Phenol from Wastewater Using Silver Nitrate Modified Activated Carbon from Groundnut (Arachis
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The equilibrium data fitted best to the Langmuir
isotherm model for the adsorption of Pb(II) on both the GSAC and MGSAC. The results also illustrated that the adsorption of Pb(II) onto both the GSAC and MGSAC fit best to the pseudo-second order.
The adsorption process was observed to be heterogeneous, exothermic and spontaneous. It can be deduced that groundnut shell is a good starting material in the production of activated carbon due to its high yield and good adsorption capacity. The modification of the activated carbon with silver nitrate is to increase the rate of adsorption, and to determine the performances of different adsorbate on the produced groundnut shell activated carbon for the investigations of the liquid phase and gaseous phase adsorption behaviours.
References: Abussaud, B., Asmaly, H.A., Saleh, A., and Kumar, V. (2015),
“Sorption of phenol from waters on activated carbon impregnated with iron oxide, aluminum oxide and titanium oxide”, Journal of Molecular Liquids, Vol.213, pp.351-359 doi:http://dx.doi.org/10.1016/j.molliq.2015.08.044
Adeniyi, A.G., and Ighalo, J.O. (2019), “Biosorption of pollutants by plant leaves: An empirical review”, Journal of Environmental
Chemical Engineering, Vol.7, pp.103-100 doi:http://dx.doi.org/10.1016/j.jece.2019.103100
Adeniyi, A.G., Ighalo, J.O., and Onifade, D.V. (2020), “Biochar from the thermochemical conversion of orange (Citrus sinensis) peel and albedo: Product quality and potential applications”, Chemistry Africa, Vol.3, pp.439-448 doi:http://dx.doi.org/10.1007/s42250-020-00119-6
Ali, A., Bilal, M., Khan, R., Farooq, R., and Siddique, M. (2018), “Ultrasound-assisted adsorption of phenol from aqueous solution by using spent black tea leaves”, Environmental Science and
Amuda, O.S., Giwa, A.A., and Bello, I.A. (2007), “Removal of heavy metal from industrial wastewater using modified activated coconut shell carbon”, Biochemical Engineering Journal, Vol.36, pp.174-181 doi:http://dx.doi.org/10.1016/j.bej.2007.02.013
Araujo, L.A., Bezerra, C.O., Cusioli, L.F., Silva, M.F., Nishi, L., Gomes, R.G., and Bergamasco, R. (2018), “Moringa oleifera biomass residue for the removal of pharmaceuticals from water”, Journal of Environmental Chemical Engineering, Vol.6, pp.7192-7199
Babarinde, A., and Onyiaocha, G.O. (2016), “Equilibrium sorption of divalent metal ions onto groundnut (Arachis hypogaea) shell: Kinetics, isotherm and thermodynamics”, Chem Int 2, Vol.2, No.1, pp. 27-46
Babatunde, E.O., Akolo, S.A., Ighalo, J.O., and Kovo, A.S. (2019), “Response surface optimisation of the adsorption of Cu (II) from aqueous solution by crab shell chitosan”, Paper presented at the
3rd International Engineering Conference, Minna, Nigeria, September 24-26, pp.1-9
Canlas, J.J., Go, J.C., Mendoza, A.C., and Dimaano, M.N. (2019), “Talisay (Terminalia catappa) seed husk biochar for adsorption of lead (II) ions in artificially contaminated soil”, In: MATEC Web of Conferences, 2019. EDP Sciences, p 04011
Eletta, O.A.A., Adeniyi, A.G., Ighalo, J.O., Onifade, D.V., and Ayandele, F.O. (2020), “Valorisation of cocoa (Theobroma
cacao) pod husk as precursors for the production of absorbents
for water treatment”, Environmental Technology Reviews, Vol.9, pp.20-36 doi:http://dx.doi.org/10.1080/21622515.2020.1730983
Eletta, O.A.A., Ayandele, F.O., Adeniyi, A.G., and Ighalo, J.O. (2019), “Valorisation of sunflower (Tithonia Diversifolia) stalk for the removal of Pb(II) And Fe(II) from aqueous solutions”, Proceedings of the 49th NSChE Annual Conference, Kaduna, Nigeria, November 13-16, pp 107-116
Eletta, O.A.A., and Ighalo, J.O. (2019), “A review of fish scales as a source of biosorbent for the removal of pollutants from industrial effluents”, Journal of Research Information in Civil
Fadzil, F., Ibrahim, S., and Hanafiah M.A.K.M. (2016), “Adsorption of lead (II) onto organic acid modified rubber leaf powder: Batch and column studies”, Process Safety and
hypogaea L) growth and yield responses to seed irradiation and mineral fertilisation”, IOSR Journal of Agriculture and
Veterinary Science, Vol.7, pp.63-70 Fauzia, S., Aziz, H., Dahlan, D., and Zein, R. (2017), “Study of
equilibrium, kinetic and thermodynamic for removal of Pb(II) in aqueous solution using Sago bark (Metroxylon sago)”, Proceedings of the 3rd International Symposium on Current
Progress in Mathematics and Sciences (ISCPMS2017), Bali, Indonesia, July 26-27, pp.1-8. doi:http://dx.doi.org/10.1063/1.5064078
Gupta, A., and Rafe, M.A. (2013), Removal of phenol from wastewater using mango peel”, International Journal of
Engineering and Technology Research, Vol.1, pp.58-62 Ighalo, J.O., and Adeniyi, A,G. (2020a), “Adsorption of pollutants
by plant bark derived adsorbents: An empirical review”, Journal
of Water Process Engineering, Vol.35, pp.101228 doi:http://dx.doi.org/10.1016/j.jwpe.2020.101228
Ighalo, J.O., and Adeniyi, A.G. (2020b), “A mini-review of the morphological poperties of biosorbents derived from plant leaves”, SN Applied Sciences, Vol.2, pp.509 doi:http://dx.doi.org/10.1007/s42452-020-2335-x
Ighalo, J.O., and Adeniyi, A.G. (2020c), “Mitigation of Diclofenac Pollution in Aqueous Media by Adsorption”, ChemBioEng
Ighalo, J.O., and Adeniyi, A.G. (2020d), “Statistical modelling and optimisation of the biosorption of Cd(II) and Pb(II) onto dead biomass of pseudomonas aeruginosa”, Chemical Product and
Process Modelling, pp.1-10. doi:http://dx.doi.org/10.1515/cppm-2019-0139
Ighalo, J.O., Adeniyi, A.G., Eletta, O.A.A., and Arowoyele, L.T. (2020a), “Competitive adsorption of Pb(II), Cu(II), Fe(II) and Zn(II) from aqueous media using biochar from oil Palm (Elaeis
guineensis) fibers: A kinetic and equilibrium study”, Indian
Chemical Engineer, pp.1-11 doi:http://dx.doi.org/10.1080/00194506.2020.1787870
Ighalo, J.O., and Eletta, A.A.O. (2020), “Recent advances in the biosorption of pollutants by fish scales: A mini-review”, Chemical Engineering Communications, p.1-12 doi:http://dx.doi.org/10.1080/00986445.2020.1771322
Ighalo, J.O., Tijani, I.O., Ajala, J.O., Ayandele, F.O., Eletta, O.A.A., and Adeniyi, A.G. (2020b), “Competitive biosorption of Pb(II) and Cu(II) by functionalised micropogonias undulates scales”, Recent Innovations in Chemical Engineering, Vol.13 doi:http://dx.doi.org/10.2174/2405520413999200623174612
Karimpour, M., Ashrafi, S.D., Taghavi, K., Mojtahedi, A., Roohbakhsh, E., and Naghipour, D. (2018), “Adsorption of cadmium and lead onto live and dead cell mass of pseudomonas aeruginosa: A dataset”, Data in Brief, Vol.18, pp.1185-1192
O.A.A. Eletta et al.: Adsorption of Pb(II) and Phenol from Wastewater Using Silver Nitrate Modified Activated Carbon from Groundnut (Arachis
hypogaea L.) Shells
35
Lütke, S.F., Igansi, A.V., Pegoraro, L., Dotto, G.L., Pinto, L.A., and Cadaval, Jr.T.R. (2019), “Preparation of activated carbon from black wattle bark waste and its application for phenol adsorption”, Journal of Environmental Chemical Engineering, Vol.7, No.5, DOI: https://doi.org/10.1016/j.jece.2019.103396
Mall, I.D., Srivastava, V.C., and Agarwal, N.K. (2006), “Removal of orange-G and methyl violet dyes by adsorption onto bagasse fly ash—kinetic study and equilibrium isotherm analyses”, Dyes
and Pigments, Vol.69, pp.210-223 Moelyaningrum, A.D. (2018), “The potential of cacao pod rind
waste (Theobroma cacao) to adsorb heavy metal (Pb and Cd) in water”, In: Sustainable Future for Human Security. Springer, pp 265-276
Olajire, A.A., Abidemi, J.J., Lateef, A., and Benson, N.U. (2016), “Adsorptive desulphuirisation of model oil by Ag nanoparticles-modified activated carbon prepared from brewer’s spent grains”, Biochemical Pharmacology, doi:http://dx.doi.org/10.1016/j.jece.2016.11.033
Olarinmoye, O., Bakare, A., Ugwumba, O., and Hein, A. (2016), “Quantification of pharmaceutical residues in wastewater impacted surface waters and sewage sludge from Lagos, Nigeria”, Journal of Environmental Chemistry and
Chattopadhyaya, M. (2015), “Synthesis and characterisation of a novel SnFe2O4 activated carbon magnetic nanocomposite and its effectiveness in the removal of crystal violet from aqueous solution”, Journal of Environmental Chemical Engineering, Vol. 3, pp.2281-2291
Rani, S., and Sud, D. (2015), “Effect of temperature on adsorption-desorption behaviour of triazophos in Indian soils”, Plant, Soil
and Environment, Vol.61, pp.36-42 Rashid, R.A., Jawad, A.H., Ishak, M.A.M., and Kasim, N.N.
(2016), KOH-activated carbon developed from biomass waste: adsorption equilibrium, kinetic and thermodynamic studies for methylene blue uptake”, Desalination and Water Treatment, Vol.57, pp.27226-27236
Sarkar, M., Acharya, P.K., and Bhattacharya, B. (2003), “Modelling the adsorption kinetics of some priority organic pollutants in water from diffusion and activation energy parameters”, Journal of Colloid and Interface Science, Vol.266, pp.28-32 doi:http://dx.doi.org/10.1016/S0021-9797(03)00551-4
Simha, P., Yadav, A., Pinjari, D., and Pandit, A.B. (2016), “On the behaviour, mechanistic modelling and interaction of biochar and crop fertilisers in aqueous solutions”, Resource-Efficient
Technologies, Vol.2, pp.133-142 Snyder, S., Lue-Hing, C., Cotruvo, J., and Jörg, E.D., Eaton, A.,
Richard, C.P., and Schlenk, D. (2010), Pharmaceuticals in the
Water Environment, National Association of Clean Water Agencies (NACWA)
Sonawane, B.K., and Korake, S.R. (2016), “Review on removal of phenol from wastewater using low cost adsorbent”, International
Journal of Science, Engineering and Technology Research, Vol.5, pp.2249-2253
Trubetskaya, A., Kling, J., Ershag, O., Attard, T.M., and Schröder, E. (2019), “Removal of phenol and chlorine from wastewater using steam activated biomass soot and tire carbon black”, Journal of Hazardous Materials, Vol.365, pp.846-856
Wang, L., Zhang, J., Zhao, R., Li, Y., Li, C., and Zhang, C. (2010), “Adsorption of Pb (II) on activated carbon prepared from Polygonum orientale Linn: Kinetics, isotherms, pH, and ionic strength studies”, Bioresource Technology, Vol.101, pp.5808-5814 doi:http://dx.doi.org/10.1016/j.biortech.2010.02.099
Yakout, S., and El-Deen, G.S. (2016), “Characterisation of activated carbon prepared by phosphoric acid activation of olive stones”, Arabian Journal of Chemistry, Vol.9, pp.1155-1162
Yang, G., Tang, L., Zeng, G., Cai, Y., Tang, J., Pang, Y., and Zhou, Y. (2015), “Simultaneous removal of lead and phenol contamination from water by nitrogen-functionalised magnetic ordered mesoporous carbon”, Chemical Engineering Journal, Vol.259, pp.854-864 doi:http://dx.doi.org/10.1016/j.cej.2014.08.081.
Authors’ Biographical Notes: Omodele A. A. Eletta is an associate professor at the
Department of Chemical Engineering University of Ilorin. She
obtained her Bachelor Degree in Chemical Engineering (1986)
from the University of Lagos, Nigeria. She also obtained her
Masters’ Degree in Chemical Engineering (1996) from the
University of Lagos, Nigeria. She had her PhD in Chemistry
(Environmental/Analytical Chemistry) (2005) from the University
of Ilorin, Nigeria. Her research interests include environmental
engineering with a special focus on the remediation of water
pollution by adsorption.
Ibrahim O. Tijani obtained a Bachelor Degree in Chemical
Engineering (2015) from Ladoke Akintola University of
Technology, Ogbomoso, Nigeria. He also obtained a Masters’
Degree in Chemical Engineering (2020) from the University of
Ilorin, Nigeria. His research interest includes environmental
pollution control with a special focus on the adsorption process.
Joshua O. Ighalo obtained a Bachelor Degree in Chemical
Engineering (2015) from the University of Benin, Nigeria. He also
obtained a Masters’ Degree in Chemical Engineering (2020) from
the University of Ilorin, Nigeria. His research interest includes
computer-aided modelling and optimisation of chemical process
systems, biofuels, solid waste management and environmental
pollution control.
T.R.M. Lalla and N. Sangster: Differences between Technicians and Engineers: An Analysis Based on UK-SPEC 36
Differences between Technicians and Engineers: An Analysis Based on UK-SPEC
Terrence R.M. Lallaa,Ψ, and Nadine Sangster b
a Department of Mechanical and Manufacturing Engineering, The University of the West Indies, St Augustine, Trinidad and Tobago; West Indies. Email: [email protected].
b Design and Manufacturing Engineering, The University of Trinidad and Tobago, San Fernando, Trinidad and Tobago; West Indies. Email: [email protected].
Ψ Corresponding Author
(Received 23 October 2019; Revised 15 June 2020; Accepted 30 July 2020)
Abstract: This work compares and contrasts the similarities and differences amongst Engineering Technicians
(EngTech), Incorporated Engineers (IEng) or Technologists, and Chartered Engineers (CEng). It examines the
competencies and commitment requirements of five (5) generic areas as specified by the United Kingdom Standard for
Professional Engineering Competence (UK-SPEC). These areas are: Knowledge and Understanding (KU); Design
and Development of processes, systems, services and products (DD); Responsibility, Management or Leadership
(RML); Communication and Inter-personal Skills (CIPS), and Professional Commitment (PC). It is found that in KU
there are two (2) similarities and eight (8) differences; in DD three (3) similarities and eight (8) differences; in RML
three (3) similarities and nine (9) differences; in CIPS there are one (1) similarity and two (2) differences and in PC
there is one (1) similarity and three (3) differences. These similarities and differences are articulated in keywords
associated by specific roles and responsibilities. The study analyses a local context of job advertisements for
recruitment based on UK SPEC, and looks at first level requirements for the five (5) generic areas of competence and
commitment and does not analyse their specific guidelines. A case study was performed in which six (6) companies’
job application advertisements were compared with that of the UK SPEC requirements for EngTech, IEng and CEng
in Trinidad and Tobago. The findings suggested that Top Management (TM) of firms to clarify the blurred lines of
roles, responsibilities and authorities between technicians and engineers. TM can use the findings of the research to
assign specific problems to either EngTech, IEng or CEng. Also, their individual skills set could be pooled to improve
the effectiveness of the teams to which they are assigned. An Engineering Competency Structure (ECS) is proposed
which could be of immense value to engineering professionals in fostering better teamwork between the two, hence
Engineering pervades the environment in which we all live, providing us with all our needs, dreams and ambitions. The technicians and engineers who make this possible enjoy contributing to teams through technical endeavor to sustain and improve lives. They possess an incredible range of creative talent that is underpinned by their enquiring minds and balanced by their intellect and judgement (UK-SPEC, 2014).
According to the Institution of Mechanical Engineers, United Kingdom (UK), “Engineering is a profession directed towards the skilled application of a distinctive body of knowledge based on mathematics, science, design, materials and manufacturing, integrated with sustainability, business and management, which is acquired through education and professional formation in a particular engineering discipline” (IMechE, 2019). It provides the technological base by which both our basic and more complex needs are developed and supplied.
Engineering qualifications and associated registration with regulatory bodies fall into one of the three (3) areas, namely: Engineer, Engineering Technologist and the Engineering Technician (UNESCO, 2003).
The exact names of the titles awarded to registered persons may differ from country to country. For instance, the Engineering Council UK registers the three tracks as Chartered Engineer (CEng), Incorporated Engineer (IEng) and Technician Engineer (EngTech), whereas Ireland registers Chartered Engineers, Associate Engineers and Engineering Technicians. In some countries, only the engineer and engineering technologist tracks are registered. In others, the registrations of engineering technicians have only recently been embarked upon (UNESCO, 2003).
In the United States of America (USA), the accrediting body for engineering programmes is the Accreditation Board for Engineering and Technology (ABET), which was formally the Engineers’ Council for
ISSN 0511-5728 The West Indian Journal of Engineering
Vol.43, No.1, July 2020, pp.36-42
T.R.M. Lalla and N. Sangster: Differences between Technicians and Engineers: An Analysis Based on UK-SPEC
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Professional Development (ECPD). The goals of the ECPD were to be “an engineering professional body dedicated to the education, accreditation, regulation, and professional development of engineering professionals and students in the United States” (ABET, 2020). These goals are achieved through programmes which are accredited when they satisfy eleven (11) general criteria. However, these criteria do not distinguish between the Technician and the Engineer and may be the cause of why there is an ongoing debate among engineering and engineering technology educators which questions where baccalaureate engineering technology (ET) graduates fit within the spectrum of engineering and technical careers (Land, 2012).
There is no doubt that technicians and engineers are to provide the competence to us with an increasingly high standard of living. Their combined efforts are generally classified under the profession of engineering. In order to perform this function, technicians and engineers must be clear regarding their roles and responsibilities required to perform their duties.
In addition to the debate regarding where engineering technology graduates fit within engineering and technical careers, there is very little literature on the appraisal of industry’s attitudes about and experiences with engineering technicians vis-à-vis engineers. In 2010, the Engineering Technology Council (ETC) of the American Society for Engineering Education (ASEE) conducted a study to compare industry experiences and attitudes about the skills and capabilities of Engineering Technicians (EngTech) versus Engineers based on the responses from two hundred (200) companies (Land, 2012). The results showed that engineering and engineering technologists are treated the same for most engineering roles.
In situations where a company hires either Technicians or Engineers into similar engineering roles, there is no guarantee that those hired perform with the same effectiveness (Land, 2012). EngTech, IEng and CEng graduates play specific roles. If these roles blur, this mighty lead to inefficiencies and ineffectiveness in their assigned jobs. This study seeks to reduce the chances of this happening by distinguishing the similarities and differences of five (5) generic areas of competencies and commitment that Engineers and Technicians must have or acquire. 2. Classification of Technicians and Engineers
According to the United Kingdom Standard for Professional Engineering Competence (UK-SPEC, 2014), ‘Technicians’ refer to Engineering Technicians (EngTech), whereas ‘Engineers’ are classified as Incorporated Engineers (IEng) and Chartered Engineers (CEng). The similarities and differences of specific roles amongst EngTech, IEng and CEng are articulated, so that engineering professionals would understand their roles
and responsibilities in teamwork and engineering management.
EngTech apply proven knowledge and understanding in solving practical engineering problems; IEng apply current and developing technology in maintaining and managing engineering design, development, manufacture, construction and operation; CEng develop apply, analyse, synthesise and evaluate solutions to engineering problems using new or existing technologies, through innovation, creativity and change. In addition, they may be technically accountable for complex systems with significant levels of risk. IEng and CEng use science, technology, engineering and mathematics at a higher level than the EngTech. 3. Competence and Commitment of Technicians and
Engineers
The UK-Engineering Council defines competence as “the ability to carry out a task to an effective standard”, and commitment as the ability to show that “they have adopted a set of values and behaviours that will maintain and enhance the reputation of the profession (UK-SPEC, 2014). To achieve competence and commitment, technicians and engineers must possess the right level of knowledge, understanding and skill in addition to a professional attitude. They must demonstrate a personal and professional commitment to society, their profession and the environment. To achieve this goal they must adopt a set of values and behaviours that will maintain and enhance the reputation of the profession.
The UK-SPEC (2014) has five (5) generic areas for assessing the competence and commitment of Technicians and Engineers. These are:
1) Knowledge and Understanding (KU) - Knowledge is “information that can be recalled” Understanding: “is the capacity to use concepts creatively”, for example, in problem solving, in design, in explanations and in diagnosis (IMechE, 2019);
2) Design and development of processes, systems services and products (DD);
3) Responsibility, management or leadership (RML); 4) Communication and inter-personal skills (CIPS);
and 5) Professional commitment (PC).
4. Similarities and Differences amongst EngTech,
IEng and CEng
Table 1 lists the roles of the EngTech, IEng and the CEng with respect to the five (5) generic areas. The descriptions of each class are in line with the general or policy requirements as indicated in the UK-SPEC. Table 2 provides a list of the keywords used to describe the roles of the EngTech, IEng and the CEng in these areas.
Firstly, two similarities are identified in the areas of Knowledge and Understanding (KU). These are:
T.R.M. Lalla and N. Sangster: Differences between Technicians and Engineers: An Analysis Based on UK-SPEC
38
Table 1. Five (5) Generic Areas of Competence and Commitment Amongst EngTech, IEng and CEng
Areas Technicians Engineers
EngTech IEng CEng
1)
Knowledge and
Understanding (KU)
- Apply proven techniques and procedures to the solution of practical engineering problems; and 1. Apply technical and practical skills; 2. Have the knowhow to do the job; 3 Be able to go beyond the immediate
requirements of the job; 4. Use initiative and experience in
solving or improving a problem or a process; and
5. Apply safe systems of work.
- Demonstrate the theoretical knowledge to solve problems in developed technologies using well proven analytical techniques; and
- Use a combination of general and specialist engineering knowledge and understanding to apply existing and emerging technology.
- Demonstrate the theoretical knowledge to solve problems in new technologies;
- Develop new analytical techniques by using a combination of general and specialist engineering knowledge and understanding; and
- Optimise the application of existing and emerging technology.
2)
Design and
Development of
processes,
systems, services
and products (DD)
- Demonstrate ability to: 1. Design; 2. Development; 3. Manufacture; 4. Construction; 5. Commissioning; 6. Operation; and 7. Maintenance.
- Application and demonstration of knowledge of known technologies and methods; and
- Apply and demonstrate theoretical and practical methods to their: 1. Design; 2. Development; 3. Manufacture; 4. Construction; 5. Commissioning; 6. Operation; 7. Maintenance; and 8. Decommissioning.
- Application and demonstration of knowledge in developing innovative products and services;
- Technically responsible for complex engineering systems; and
- Apply and demonstrate theory and practical methods to the analysis and solution of problems.
3)
Responsibility,
Management
and Leadership (RML)
- Demonstrate supervisory or technical responsibility; and
- Able to show personal responsibility in seeing a process through to completion within specifications.
- Demonstrate responsibility for project management while leading and developing other professional staff; and
- Provide technical and commercial management.
- Accountable for project, finance and personnel management;
Conduct cost/benefit analysis between technical and socio-economic factors; and
- Provide technical and commercial leadership.
4)
Communication
and
Interpersonal Skills (CIPS)
- Show how the individuals: 1. Take part in discussions; 2. Make presentations; 3. Synthesise information; and 4. Be able to develop documents.
- Demonstrate effective interpersonal skills.
- Demonstrate effective interpersonal skills.
5)
Professional
Commitment (PC)
- Personal commitment to: 1. Become part of the profession; 2. Upload standards; 3. Code of Conduct; and 4. Obligation to society, profession,
and environment
- Commit to and demonstrate professional values and standards respectively; and
- Show obligations to society, the profession and the environment.
- Be able to communicate technical matters;
- Commit to professional values; and standards respectively; and
- Show obligations to society, the profession and the environment.
Source: Modified from UK-SPEC (2014)
Table 2. Keywords used to distinguish EngTech, IEng and CEng
Areas EngTech, IEng CEng
1)
Knowledge and
Understanding
(KU)
Apply General Existing
Technical and practical Initiative and experience Solve
Apply Demonstrate General Specialist Existing
Emerging Analytical Techniques Combination Solve
Apply Demonstrate General Specialist Existing Emerging
Leading Developing Professional Technical Commercial
Accountable Project Finance Personnel Management
Trade-offs Technical Socio-economic
T.R.M. Lalla and N. Sangster: Differences between Technicians and Engineers: An Analysis Based on UK-SPEC
39
Table 2. Keywords used to distinguish EngTech, IEng and CEng (Continued)
Areas EngTech IEng CEng
4)
Communication
and
Interpersonal
Skills (CIPS)
Show Contribute Discussions Presentation Read
Synthesise Write Information Documents
Demonstrate Effective
Interpersonal Skills
Demonstrate Effective
Interpersonal Skills
5)
Professional
Commitment
(PC)
Personal Commitment Become Part of Profession Professional Institution
Code Standards Conduct Recognise Obligation Society Environment
Demonstrate Personnel Commitment Professional Standards Recognising
Obligation Society Profession Environment
Demonstrate Personnel Commitment Professional Standards Recognising
Obligation Society Profession Environment
1) EngTech, IEng and CEng must use KU to solve engineering problems; and
2) EngTech, IEng and CEng must use existing KU.
There are also several differences identified in KU as follows:
1) EngTech focus on practical problems, while IEng and CEng are trained to solve problems of diverted grounds;
2) EngTech rely on technical and practical skills in addition to initiative and experience while IEng and CEng rely on theoretical and analytical skills ;
3) EngTech use existing technology, IEng use existing and emerging technology while CEng use existing, emerging and new technology;
4) EngTech must have general KU while IEng and CEng must have a combination of general and specialist KU;
5) CEng alone are required to optimise the application of existing, emerging and new technology;
6) EngTech must apply KU, while IEng and CEng must apply and demonstrate KU;
7) EngTech have general KU, while IEng and CEng have general and specialist engineering KU;
8) Emphasis is placed on EngTech to apply safe systems of work.
Having regards the similarities and differences of KU, the EngTech must be a specialist in practical matters relating in his/her chosen field. The IEng must work with the EngTech in managing day-to-day operations. The CEng must work with both EngTech and IEng in ensuring that the effectiveness and efficiency of operations are continually improved.
Secondly, for the areas of Design and Development of processes, systems, services and products (DD), several similarities are identified. These are:
1) EngTech, IEng and CEng use DD for processes , systems, services and products;
2) EngTech and IEng design, develop, manufacture, construct, commission, operate, and maintain; and
3) EngTech and CEng are required to use practical and theoretical methods in DD.
On the other hand, the main differences identified in DD are:
1) Emphasis is placed on the EngTech to design and develop equipment;
2) EngTech contribute and demonstrate while IEng and CEng apply and demonstrate; CEng also innovates;
3) IEng and CEng use practical and theoretical methods;
4) IEng apply decommission and re-cycle; 5) IEng use established technologies to deliver
projects; 6) CEng design and develop innovative products and
services; 7) CEng are technically responsibility for complex
engineering systems; 8) CEng analyse, synthesise, and evaluate solutions to
engineering problems. In essence, the EngTech contribute to DD; the IEng
work with the EngTech in using DD for solving routine problems. The CEng are directly responsible for using DD for solving complex or non-routine problems.
Thirdly, regarding the area of Responsibility, Management and Leadership (RML), the EngTech act in a Supervisory role, whereas the IEng act as a Manager, and the CEng as a Leader. The main similarities amongst them include:
1) EngTech, IEng and CEng must be technical; 2) EngTech and IEng demonstrate technical skills; and
3) IEng and CEng deal with projects and finance. There are also several differences identified. These
are: 1) EngTech have supervisory or technical
responsibility; 2) EngTech have personal responsibility for ensuring
that the process is completed according to specifications;
3) EngTech and IEng have responsibility while CEng has accountability;
4) IEng demonstrate responsibility for management; 5) IEng has some responsibility for providing
leadership to other professional staff;
T.R.M. Lalla and N. Sangster: Differences between Technicians and Engineers: An Analysis Based on UK-SPEC
40
6) IEng provide technical and commercial management;
7) CEng are accountable for project, finance and personnel management;
8) CEng manage tradeoffs between technical and social economic factors; and
9) CEng provide technical and commercial leadership.
Fourthly, for the area of Communication and Interpersonal Skills (CIPS), EngTech, IEng and CEng share the same role i.e., must be able to communicate and have interpersonal skills. On the difference side, EngTech must show CIPS through contributing to discussions, making presentations, reading and synthesising information and writing different types of documents while IEng and CEng must demonstrate effective CIS in every aspect of their work. In short, EngTech is responsible for his/her personal conduct, while the IEng and CEng are equally responsible for the overall conduct of the organisation.
Lastly, within the context of Professional Commitment (PC), EngTech are responsible for his/her personal development, while the IEng and CEng are equally responsible for the overall development of the organiation. One similarity in the area is that EngTech, IEng and CEng must have professional commitment. On the other hand, there are several differences identified, including:
1) EngTech make a personal commitment by becoming a professional, while IEng and CEng must demonstrate a personal commitment through actual work with others and the society;
2) EngTech make personal commitment to (a) the Code of conduct; and (b) an obligation to society, profession and the environment; and
3) IEng and CEng demonstrate commitment to (a) the professional standards; and (b) the obligations to society, profession and the environment.
Based on above analyses, it can be deduced that the work in each role is analogous to the responsibilities of the technician, manager and leader, respectively. The practical implication of this is that, engineering programmes whose goals are to produce either one or a combination of these positions can design and tailor their programmes to match the requirements of the technician, manager or leader. In this way, academic institutions, employers and accrediting bodies will become more aligned to the demands of industry.
5. A Case Study Based on the UK-SPEC
A case study was performed using six (6) engineering companies (i.e., A, B, C, D, E, and F) in Trinidad and Tobago (T&T). Job application advertisement forms for EngTech, IEng and CEng positions were obtained.. It was intended to analyse a local context of job advertisements for recruitment to see how much they complied with the UK SPEC key words. The study looked at first level requirements for the five (5) generic
areas of competence and commitment but would not analyse their specific guidelines.
Based on the case analysis, Companies A and B had similar requirements for the EngTech position, C and D for the IEng position and D and E for the CEng position. The keywords from the advertisement of each type of profession were obtained. The keywords used were compared with the roles of EngTech, IEng and CEng with respect to the five areas of KU, DD, RML, CIPS, and PC. Tables 3 and 4 show the relationship for the EngTech requirements for companies A and B, and the IENG requirements for companies C and D, respectively.
From Table 3, Companies A and B had advertised for an EngTech in which the successful applicant must have KU in thirteen (13) of the twenty-two (22) required areas of expertise; DD in four (4); CIPS in one (1); and PC in one (1). This indicated that EngTech have been called upon to perform tasks that they have not qualified to do.
Table 3. Keywords Used for EngTech in Companies A and B
From Table 4, Companies C and D have been asking for IEng with expertise in KU in five (5) of the twenty-three (23) requirements, DD in four (4); RML in four (4); CIPS in seven (7) and three (3) in PC. Again as showed in the case with the EngTech profile, several expertise asked for would not be in the expertise areas of their applications. In this case, the two (2) missing areas were ‘trouble shooting’ and ‘repair’.
While extending the analysis to the relationship for the CEng requirements for companies E and F, the findings are summarised in Table 5. Results show that there were twenty-six (26) requirements for CEng. KU had six (6), DD had five (5); RML had nine (9); CIPS had five (5), and PC three (3). Moreover, it is observed
that for three (3) types of engineering jobs (EngTech,
IEng and CEng), each would be required to perform the roles and responsibilities of the other two (2).
y y
KU DD RML CIPSPC KU DD RML CIPSPC KU DD RML CIPSPC
Service
Repair
Install
Overhaul
Expedite
Minimise
Assist
Maintain
Inspect
Troubleshoot
Replace
Follow requlations
Read and work
Test
Adjust
Support
Skilled
Calibrate
Modifies
Plans
Informs
Configures
IENG CENGCompany A,B
ENGTECH
Eng Tech
T.R.M. Lalla and N. Sangster: Differences between Technicians and Engineers: An Analysis Based on UK-SPEC
41
Table 4. Keywords Used for IEng in Companies C and D
Table 5. Keywords Used for CEng in Companies E and F
6. A Proposed Engineering Competency Structure
Figure 1 depicts a proposed Engineering Competency Structure (ECS) that shows the relationship amongst the core skillsets of the engineering professionals, including, the engineering technician, the incorporated engineer and the chartered engineer. The five (5) generic areas constitute the structure that could be used to build an organisation which fit persons with the relevant qualifications to posts or jobs in the industry.
For KU, EngTech solve practical problems while IEng and CEng handle problems of diverted grounds. EngTech have skills based on practical experience, while
EngTech and CEng have theoretical and analytical skills. EngTech possess KU of existing technology, IEng possess KU of existing and emerging technology, and CEng have KU of existing, emerging and new technology. EngTech have general KU, while IEng and CEng have general and specialist KU. EngTech apply while IEng and CEng demonstrate KU. EngTech apply safe systems of work.
EngTech contribute to DD, while IEng apply and demonstrate DD and CEng innovate. IEng deliver projects while CEng design and develop products and services. CEng take responsibility for complex DD and solving engineering problems.
For RML, EngTech have taken responsibility, while IEng manage and CEng lead. EngTech have personal responsibility; IEng have some responsibility for leading and developing others, while CEng are accountable for personnel management. IEng have some responsibility for commercial management, while CEng have accountability for commercial leadership.
In areas of CIS, EngTech must be able to read, write, discuss, synthesise and make presentations, while IEng and CEng must demonstrate effective CIS. Lastly, it is the personal responsibility of the EngTech to make a professional commitment (PC), while IEng and CEng demonstrate professional commitment.
Figure 1. An Engineering Competency Structure (ECS)
7. Conclusion
The analysis of the similarities and differences amongst the five generic areas of the UK- SPEC shows that there are more differences than similarities, indicating that the roles and responsibilities of each are separate and distinct. These similarities and differences are articulated in keywords associated by specific roles and responsibilities (see Table 2). These keywords can be used by top management and supervisors in developing
KU DD RML CIPSPC KU DD RML CIPSPC KU DD RML CIPSPC
Monitoring
Coordinating
Planning
Operations
Cost
Quality
HSE
Process control
Collect
Analyse
Maintain
Direct
Liase
Train
Develop
Leadership
Trouble shooting
Work ethic
Team
Reporting
Writing skills
Assist
Repair
Company C, D
IENG
Eng Tech IENG CENG
KU DD RML CIPSPC KU DD RML CIPSPC KU DD RML CIPSPC
Support
Integrity
Sustainance
Cost effective
Design
Opportunities
Drive
Optimization
Continuous
Improvement
Coordinate
Manage
Coach
Mentor
Prioritise
Business
Develop
Deliver
Specialized
Accountable
Cross discipline
Integrate
Advise
Conduct
Lead
Review
Technical
Company E,F
CENG
Eng Tech IENG CENG
T.R.M. Lalla and N. Sangster: Differences between Technicians and Engineers: An Analysis Based on UK-SPEC
42
job descriptions and assigning work instructions and in performance appraisals. They would give careful consideration when matching job specifications to required qualifications in performing most engineering roles
A case study was conducted involving six (6) engineering companies in Trinidad and Tobago. Their advertisements for EngTech, IEng and CEng were analysed, with respect to their keywords (which were compared with the keyword in Table 1). It was found that each type of engineering professional was required to perform the functions of the others. Individual skills set could be pooled to improve the effectiveness of the teams to which they are assigned. The study explored the similarities and differences amongst EngTech, IEng and CEng from a local context of job advertisements for recruitment based on the UK-SPEC. The proposed ECS could be of immense value to engineering professionals in fostering better teamwork between the two, hence increasing their effectiveness and efficiencies.
References:
ABET (2020), “About ABET: History”, Accreditation Board for Engineering and Technology, available at: https://www.abet.org/about-abet/history/, Accessed on 28 July 2020
Land, R.E. (2012), “Engineering technologists are engineers”, Journal of Engineering Technology, Spring, pp.32-39
IMechE (2019), The Institution of Mechanical Engineers.
Academic Accreditation Guidelines, Institution of Mechanical Engineers, London, September.
UK-SPEC (2014), The United Kingdom Standard for Professional
Engineering Competence, 3rd Edition, The Engineering Council, available at: www.engc.org.uk
UNESCO (2003), Engineering: Issues, Challenges, and
Opportunities for Development, UNESCO Publishing, The United Nations Educational, Scientific and Cultural Organisation, Paris, France.
Authors’ Biographical Notes:
Terrence R.M. Lalla received his PhD in Mechanical
Engineering from The University of the West Indies. Dr. Lalla is a
lecturer in the Department of Mechanical and Manufacturing
Engineering at The University of the West Indies (UWI), St.
Augustine Campus. His areas of research are engineering
management, quality assurance, and sustainable engineering.
Nadine Sangster received her PhD in Mechanical Engineering
from The University of the West Indies in 2008. She is an Assistant
Professor in the Design and Manufacturing Unit at The University
of Trinidad and Tobago, O’Meara Campus. Her research interests
are fuzzy logic and its application to complex plants and the use of
smart technologies in agriculture and mechatronics with an
emphasis on advanced manufacturing technologies.
A. Koonj Beharry and K.F. Pun: Contextual Analysis of Innovation Process Models toward the Fourth Industrial Revolution 43
Contextual Analysis of Innovation Process Models toward the Fourth
Industrial Revolution
Ambika Koonj Beharry a,Ψ, and Kit Fai Pun b
Department of Mechanical and Manufacturing Engineering, The University of the West Indies, St Augustine, Trinidad and Tobago; West Indies.
The etymology of the word ‘innovation’ dates back to the mid-fifteenth century. The Etymology Dictionary traces the origin of the word from the Late Latin ‘innovationem’, a noun of action which stems from the past participle ‘innovare’ meaning ‘to change or to renew’. Another school of thought attributes the origin to the Latin ‘novus’ which translates as ‘new’ (Bagherinejad, 2006). There exists no universally accepted definition of the term ‘innovation’. Existing definitions of innovation are as diverse as the disciplines that put forward an explanation of the concept, and are therefore influenced by the context of its origin (Srivastava, 2015).
Garcia and Calantone (2002) assert that the plethora of definitions of the concept lead to ambiguity in its utilisation in the literature and its operationalisation in empirical research. Crossan and Apaydin (2010) propose a ‘multi-level approach’ across societal, organisational and individual levels, due to lack of a singular theory which could operate at all levels simultaneously. The diverse streams of innovation research have led to the
consideration of innovation across multiple domains (Avermaete et al. 2003). Innovation models have evolved over time and represent the range of activities undertaken during the innovation process. This paper explores the recurring contextual themes based on a comparative analysis of innovation models and processes advocated in literature. The key stages and elements of innovation processes at the firm’s level are explored and their implications for firms operating in the fourth industrial revolution are discussed. 2. Taxonomies of Innovation
2.1 The Multi-Disciplinary Thinking
The multi-disciplinary approach explores innovation through the lens of individual disciplinary specialisations. According to Godin (2008), from a technological perspective, German economist, Joseph Schumpeter, regarded as a pioneer in the field of innovation theory, defines innovation as “a new
combination of means of production, that is, as a change
in the factors of production (inputs) to produce products
(outputs).” From a developmental perspective, Arais-
ISSN 0511-5728 The West Indian Journal of Engineering
Vol.43, No.1, July 2020, pp.43-54
A. Koonj Beharry and K.F. Pun: Contextual Analysis of Innovation Process Models toward the Fourth Industrial Revolution
44
Aranda et al. (2001) define innovation as “the creative
process through which new products, services or
production processes are developed”. From a knowledge perspective, du Plessis (2007) defines innovation as “the
creation of new knowledge and ideas to facilitate new
business outcomes, aimed at improving internal business
processes and structures and to create market driven
products and services”. From a team-based perspective, Goyal and Akhilesh (2007) define innovation as “the
successful implementation of creative ideas within an
organisation [whereby] creativity from individuals and
teams serves as a starting point for innovation”. Laforet and Tann (2006) noted the existence of three
streams in innovation research. The first stream is the economic-oriented stream which highlights the importance of small and medium-sized enterprises (SMEs) as a driving force for innovation and being equally innovative as larger firms. The second stream is the organisation-oriented stream which prescribed a number of organisational factors that small business owners could use to enhance organisational performance, and the third stream is the project-oriented stream which viewed customers as important sources of innovation.
In comparing the main streams of innovation, similarities are found between 1) the developmental perspective and the economic-oriented stream which focus on innovation processes of firms, 2) the knowledge perspective and the organisation-oriented stream which concentrate on knowledge sharing activities within the organisation, and 3) the team-based perspective and the project-oriented stream which are people-based approaches to innovation. There exists a link between the streams of innovation research and the perspective definitions of innovation. Across all streams/disciplines, organisational learning is implicitly practiced though not necessarily explicitly managed.
2.2 The Multi-Dimensional Thinking
From the multi-dimensional thinking, innovation examines the impact on various strata that result from changes in the operational characteristics of a firm. According to Schumpeter (1934), these “new combinations” lead to innovation in five (5) distinct dimensions, namely, product, process, market, source and organisation. Similarly, the OECD (2005) Oslo Manual (3rd Ed.) considers innovation along four dimensions brought about through “changes in its methods of work, its use of factors of production and the types of output that improve its productivity and/or commercial performance.
Several distinctions of the dimensions are observed. Firstly, the Oslo Manual extends Schumpeter’s definition of ‘product innovation’ to include services. Secondly, the Oslo Manual’s definition of ‘process innovation’ includes methods of delivery unlike Schumpeter who focused primarily on methods of production. Thirdly, Schumpeter considers ‘market innovation’ vis-a-vis the
Oslo Manual’s ‘marketing innovation’ which focuses on marketing as a means to new markets. Fourthly, Schumpeter looks at ‘organisation innovation’ from an inter-firm perspective, while the Oslo Manual looks at ‘organisational innovation’ which includes intra-firm operations of the organisation. Finally, unlike Schumpeter, the Oslo Manual does not consider ‘source innovation’.
The Oslo Manual largely concurs with Lundvall’s (1992) definition (as cited by Avermaete et al, 2003) which states that innovation is an ongoing process of leaving, searching and exploring which results in: (1) new products; (2) new techniques; (3) new forms of organisation; and (4) new markets. Moreover, Tidd et al. (2005) propose the ‘4Ps’ of innovation from the perspective of ‘change’ along the four (4) dimensions, as follows:
1. Product – Change in the product/service offered 2. Process – Change in the methods of creation and
delivery 3. Position – Change in the target market/market
strategy 4. Paradigm – Change in the operational intention
The dual concepts of ‘new’ and ‘change’ are explained by two distinct modes of innovation espoused in the literature namely, radical innovation and incremental innovation (Lin and Chen, 2007; Zhao, 2005). Oke et al. (2007) define radical innovation from a market perspective as the introduction of a new product to an existing market and the introduction of a new product to a new market whereas they define incremental innovation from a product perspective as minor and major improvements to existing products.
2.3 The Process Thinking
The process thinking toward defining innovation considers all activities along the “innovation value chain” (Hansen and Birkinshaw, 2007). Kline and Rosenberg (1986) assert that innovation is a non-linear process owing to its susceptibility to various change factors. Tidd et al. (2005) agree that a linear approach to innovation simplifies the complexities arising from interaction between ‘technology push’ and ‘need pull’ activities.
Moreover, Cumming (1998) asserts that there are three basic steps in the innovation process starting with the idea generation followed by successful development of the idea into a useable concept and culminating in successful application of the concept. Ahmed (1998) describes innovation as a three-phase process, starting with idea generation progressing onto idea validation and ending with commercialisation. Similarly, Hansen and Birkinshaw (2007) propose that innovation is an “integrated flow” across the three phases of idea generation, conversion and diffusion. The idea of integrated flow is affirmed by Roper et al. (2008) who consider innovation as an intermediary event linking
A. Koonj Beharry and K.F. Pun: Contextual Analysis of Innovation Process Models toward the Fourth Industrial Revolution
45
precursory knowledge management activities and preceding value creation activities.
3. Evolution of Innovation Concepts across the Four
Industrial Revolutions
Regardless of the innovation context, technological innovations have been the driving force of industrialisation. This is evidenced by four (4) major technological breakthroughs that have influenced the mode of production in the global manufacturing sector (Naudé, and Adam Szirmai, 2012). These developments have led to the successive progression of four (4) industrial revolutions since the second half of the eighteenth century. Figure 1 maps the innovation-industrialisation relationship from the perspective of technological innovation leading industrialisation.
The Fourth Industrial Revolution (4IR) brings with it a unique set of opportunities and challenges which have significant implications for industry, labour and governments (Schwab, 2016). While technological innovations have set the pace for industrialisation, the converse is also true. Industrialisation has in turn stimulated innovation in the form of emerging technologies and technological developments (Schwab, 2016), resulting from new combinations of technologies (Lee et al., 2018; Nicolov and Badulescu, 2012). Figure 1. Mapping of the Innovation-Industrialisation Relationship
According to Verloop (2004), innovation during the pre-industrial era was ad-hoc and lacked scientific and technological applications. The onset of the industrial era changed the innovation landscape by introducing technology-driven processes which have since transitioned into opportunity-driven processes. Opportunity-driven innovation is the mainstay of the 4IR resulting from exponential increase in speed and scope of impact from technological breakthroughs (Schwab, 2016).
Rothwell’s (1994) seminal work on the ‘fifth-generation innovation’ concept has pioneered the characterisation of innovation models throughout the industrial era (Hobday, 2005; Tidd, 2006). Based on his classification, innovation was considered as a linear process during the first and second generations however, the focus of the first generation was on technological development (technology-push) while in the second-
generation emphasis was placed on market demand (need-pull). The third-generation innovation process saw a “coupling” of the push-pull factors along a “logically
sequential, though not necessarily continuous process,
that can be divided into a series of functionally distinct
but interacting and interdependent stages” (Rothwell, 1994).
However, Hobday (2005) argues that the transition from one generation to the other does not imply a discontinuation of models from the previous generation but rather an expansion of models that co-exist and intersperse. This is evident in the disparity between developing and developed economies. Innovation in developing countries, such as the Caribbean, emerges from “behind the technology frontier” as defined by leading industrially advanced countries (IACs). Hobday (2005) asserts that innovation process models across these five generations are presented from the perspective of the research and development (R&D)/technology developers, usually from the developed economies, and does not take into account the distinct innovation process of R&D/technology adopters, such as the developing countries. Marinova and Phillimore (2003) build upon Rothwell’s (1994) five generations of innovation models by broadening Rothwell’s typology and introducing a sixth generation of innovation. The scope of Rothwell’s analysis occurs at the firm level while Marinova and Philimore’s analysis extends to the economy level. A decade later, Kotsemir and Meissner (2013) present another perspective on the evolution of innovation models and further extend the classification to include an emerging seventh generation of innovation models.
Chesbrough (2003) pioneered what he termed “the era of open innovation”. The major premise of open innovation is the decentralisation, diffusion and distribution of both internal and external R&D capabilities via inflows and outflows of knowledge-based competencies (Chesbrough, 2011). The open innovation model encourages interaction with external R&D networks toward leveraging internal R&D capabilities (Salter et al., 2014) through integrated “technology acquisition” and “technology exploitation” (Van de Vrande, 2009) unlike the first five generations of innovation models which focused primarily on technology development (Hobday, 2005).
Across the generations, innovation models have evolved from single-dimensional models to more complex multi-dimensional models. Eveleens (2010) describes the evolutionary trend of innovation models as becoming more intricate, interdisciplinary and interconnected as a result of the increasing complexity of the operating environment. Single-dimensional models consider the innovation process as a “linear sequence of functional activities”, while multi-dimensional models account for the innovation process as a set of interactive cross-functional intra- and inter-firm activities (Tidd et al, 2005).
A. Koonj Beharry and K.F. Pun: Contextual Analysis of Innovation Process Models toward the Fourth Industrial Revolution
46
Based on the timescales presented by Kotsemir and Meissner (2013), the generations of innovation models are superimposed onto the timeline of the four (4) Industrial Revolutions to illustrate the innovation – industrialisation relationship. It is observed that the formalisation of innovation process thinking began toward the end of the technology-driven phase of the industrial era which coincided with the end of the Second Industrial Revolution (2IR), while most of the innovation models classified thus far have emerged during the Third Industrial Revolution (3IR). Marinova and Philimore (2003)’s sixth generation Innovative Milieux model as well as Kotsemir and Meissner (2013)’s seventh generation Open Innovator model transition into the 4IR. 4. Review of Innovation Process Models
This section presents a chronological review of nine (9) innovation models between 1985 and 2007 spanning the 3IR and 4IR. The models are assessed in the context of the 4IR which is characterised by digital transformations integrating technology, market and society (Lee et al., 2018) and the application of the Internet of Things (IoT) to the creation of industrial value (Kiel et al., 2017) via distributed value chains (Lee et al., 2018). 4.1 Rothwell and Zegveld (1985) Coupling Model
During the third generation of innovation processes Rothwell and Zegveld (1985), as cited by Rothwell (1994), present the coupling model of innovation. The coupling model of innovation essentially combined the first- and second-generation innovation processes to account for both technology push and market pull forces. Like its predecessors, the third-generation innovation model was basically a series of sequential but not necessarily continuous stages. A major distinction between the coupling model and its predecessors was the inclusion of intra- and extra-organisational feedback loops. According to Rothwell (1994), success is dependent of efficient management of several project-level and corporate-level factors. Project-level factors include effective communication among all endogenous and exogenous actors in the process, the appointment of idea champions and organisational learning. Corporate-level factors include management support for innovation, flexibility and responsiveness to change and an accommodating culture. Rothwell (1994) stresses the human element at the core of a successful innovation effort.
Key
po
ints
fo
r co
nsi
der
atio
n
Based on Rothwell and Zegveld’s (1985) model, key points that emerge for consideration: - the need for consideration of both technology push and
market pull factors; - the need for effective communication among all
participants in the process; - the need for management support for innovation and - the need for competent individuals to champion the
initiative.
While Rothwell and Zegveld’s (1985) model emerges in the 3IR, it combines two of the three integrated components of the 4IR as identified by Lee et al., (2018) – technology and market. The emphasis on effective communication among actors in the process is enabled by the preponderance of digital technologies in the 4IR. 4.2 Cooper’s (1990) Stage-Gate System
Cooper (1990) proposes a linear five-phase stage-gate system built upon a process-management approach. The basis of this model is a focus on the production process toward the removal of variances within the process with the intention of improving the quality of the output. A stage-gate system consists of a series of predefined activity-based stages that take the process from idea to launch. Between each stage is a gate which acts as a checkpoint with specified criteria and deliverables. The use of the checkpoint system creates a linear process and appears to circumvent the need for feedback loops in Cooper’s (1990) model. Two caveats are presented in Cooper’s (1990) stage-gate system:
1. Stage-gate systems usually range from four to seven stages and gates depending on their specific application and
2. The typical five-stage (five-gate) system can be adapted to model an innovation process by setting appropriate activity-based stages as well as relevant criteria and deliverables at each gate.
Key
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Based on Cooper’s (1990) model, key points that emerge for consideration: - the need for a flexible system in terms of the number
and nature of stages and gates dependent on the application, and
- the need for thorough checkpoints with appropriately defined criteria and deliverables to ensure continuous alignment along the process toward the endpoint.
The operationalisation of distributed networks in the
4IR wherein actors along the value chain function independently within an integrated system (Lee et al., 2018, draws on the need for continuous alignment along the process to ensure the desired outcome is achieved. System flexibility is inherent in the size and composition of the distributed network. 4.3 Ahmed’s (1998) Three-Phase Innovation Model
Ahmed (1998) describes innovation as a holistic process comprised of three distinct recurrent and concurrent phases. First is the idea generation phase in which ideas emerge, many of which do not proceed to the second stage. Second is the idea rationalisation phase which utilises an internal control stage-gate system with feedback loops to determine the feasibility of ideas and their compatibility with organisational goals. Ahmed’s (1998) model uses a variation of Cooper’s (1990) linear stage-gate system by including cyclical feedback loops.
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The third and final stage in the process is the commercialisation of the viable idea(s) with the aim of value extraction. The effectiveness of this process depends on the firm’s ability to provide the appropriate culture and climate conducive to innovation and stresses that such culture should be aligned with the firm’s organisational goals (Ahmed, 1998). This link between innovation culture and organisational goals suggests that characteristics of an innovation culture would be unique to a particular firm.
The culture and climate foster innovativeness. Ahmed (1998) distinguishes culture as “a primary determinant of innovation” and further suggests that positive cultural characteristics are critical to a firm’s ability to innovate. This view is substantiated by Allee and Taug (2006), who suggest that Western firms need to inculcate innovativeness in their culture and structure if they are to sustain their competitiveness and growth. The iterative nature of Ahmed’s (1998) model suggests that there is room for continuous improvement and refinement of ideas throughout the process. The second stage of this model is critical to successful innovation since an alignment between external environmental factors and organisational strategy is a determinant of organisational performance (Alam, 2006) and the foundation of a robust innovation culture and competitiveness (Ulusoy et al., 2015; Garcia-Morales et al., 2006).
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Based on Ahmed’s (1998) model, key points that emerge for consideration: - the need for the establishment of a culture that
facilitates innovation since appropriate organisational culture is the catalyst for idea generation which is the seed of innovation;
- the need for innovation culture to align with organisational goals in the context of the external operating environment, and
- the need for the innovation process adopted by a firm to allow for continuous improvement and refinement of ideas that are feasible for commercialisation.
The focal point of Ahmed’s (1998) innovation model
is organisational culture to foster innovation. Among the stated elements of innovation culture is adaptability. The rate of change and span of impact of the 4IR (Schwab, 2016) require organisations to be change tolerant as opposed to change averse and ensure that adequate and appropriate resources are available to respond to changes in the external operating environment (Ahmed, 1998). Schwab (2016) endorses the need for organisations to re-evaluate their culture in light of the changing operational environment. 4.4 Cumming’s (1998) Model of Elements for
Innovation
Cumming (1998) uses the engineering concept to identify the factors that affect the innovation process. Cumming (1998) expands on the three-stage innovation
model discussed by Ahmed (1998) by including the elements required for innovation at each stage. There are some notable differences between these two innovation models. Cumming (1998) justifies the need for an environment that facilitates creativity as this affects the quality and quantity of the ideas generated. However, while Ahmed’s second stage seeks to align ideas with organisational goals, Cumming’s second stage focuses on refining ideas generated in the first stage directly with the end user in mind. This customer-centric perspective is an example of a market-pull model.
While the final stage of Ahmed’s innovation process focuses on value extraction through commercialisation of an idea, the final stage of Cumming’s innovation model concentrates on application through market testing in an effort to understand the needs of the customer, so as to avoid premature failure of a potentially feasible idea. Cumming (1998) highlights that gaining an understanding of the customers’ needs does not guarantee success of the idea however, a lack of understanding of the customers’ needs will almost certainly result in failure of the idea. This suggests that market research and market testing are critical to the innovation process and should be conducted during implementation but before full-scale commercialisation of the idea. While Ahmed (1998) emphasises culture as a key enabler of innovation, Cumming (1998) focuses on technology as the key component to bridge the gap from idea generation to successful implementation.
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Based on Cumming’s (1998) model, key points that emerge for consideration: - the need for market testing as an important stage in the
implementation of a concept before full-scale commercialisation in the market as this ensures that the market is capable of successfully absorbing the innovation;
- the need for feedback and review of ‘system errors’ and - the need for technology considerations as a key enabler
of the innovation process.
Just over a decade later, Cumming (1998), like
Rothwell and Zegveld (1985) return emphasis to technology and market considerations.
4.5 Gaynor’s (2002) Four-Stage Systems Model
Gaynor (2002) advocated a four-stage systems model of innovation that is an extension of Cooper’s (1990) stage-gate system. The model includes a post-implementation review phase which assimilates the new product into the organisation and terminates the ‘project’. This phase also incorporates organisational learning. It considers project management issues as an important ingredient which bridges the gap between concept development and extraction of value from the concept via product launch.
Another notable difference of this model is the elimination of infeasible ideas at the first idea generation stage unlike the previously discussed three-stage models in which ‘knockouts’ occur during the second idea
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development stage. A perceived strength of this model is the distinction between pre-project activities and project activities.
While Ahmed’s (1998) model considers commercialisation as the only means of extracting value from the concept, Gaynor’s (2002) product launch stage is a more holistic approach to value extraction and considers commercialisation as one factor in this process. Moreover, Gaynor (2002) emphasises the sentiment of culture as an important ingredient in the recipe for successful innovation as suggested by Ahmed (1998) and Cumming (1998). However, unlike Ahmed’s (1998) model which has a feedback mechanism at the internal idea development phase, this model considers feedback at the external product launch phase based on end-user response.
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n Based on Gaynor’s (2002) model, key points that emerge
for consideration: - the need for consideration of design validation and
project management issues as part of the innovation process, and
- the need for customer input to drive product optimisation.
The customer-oriented focus of Gaynor’s (2002)
model aligns with the evolving role of the customer as the driver of innovation (Schwab, 2016) particularly considering the shortening of the gap between the firm and its customer in a disrupted network (Lee et al., 2018). 4.6. Chesbrough’s (2003) Open Innovation Model
Chesbrough (2003, 2012) changed the innovation landscape by introducing his open innovation model resulting in a paradigm shift which opened new vistas for research and development of ideas by transforming the boundary of the firm from a closed rigid structure to an open penetrable structure. The concept of the open innovation model allows firms to capitalise on opportunities beyond its boundaries and limited internal capabilities. This holds true from both the research and development (market) domains. The foundation of the open innovation model is knowledge-sharing within and across firms.
This knowledge-sharing approach allows firms to profit from others’ use of their IP as well as from their use of others’ IP thereby generating optimal use of internal and external ideas, technologies and markets (Chesbrough, 2003). The open innovation approach would minimise the risk of missed opportunities which occurs when potential ideas do not align with organisational goals. Chesbrough (2003) cites the case of Xerox which failed to capitalise on research in computer hardware and software technologies because they were not aligned with its core competency in printers and copiers.
Moreover, Gassmann and Enkel (2004) propose three archetypes of open innovation processes – 1) the outside-in process which is the integration of external knowledge into internal operations; 2) the inside-out process which involves the transfer of ideas to the external environment and 3) the coupled process combines activities of the outside-in and inside-out processes and requires cooperation among internal and external partners.
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Based on Chesbrough’s (2003) model, key points that emerge for consideration: - the open innovation model contradicts the notion that
ideas worth pursuing should be aligned with organisational goals/strategy;
- the importance of knowledge-sharing between firms, particularly in the Fourth Industrial Revolution where organisational boundaries are becoming less rigidly defined (Schwab, 2016), and
- the need for alliances with other firms to capitalise on a potentially viable idea outside the core competencies of the firm.
Chesbrough’s (2003) Open Innovation model comes
as a turning point between the 3IR and the 4IR. This model seems to lead the emergence of the distributed network where firms act outside of their boundaries and competencies. 4.7 Tidd et al.’s (2005) Innovation Process Model
Tidd et al. (2005) present an innovation process model which incorporates a number of features models previously discussed. The first stage involves searching and scanning the internal and external environments for new opportunities however, the increasing volume of information being generated can result in ‘noise’ infiltrating the system and drowning out potentially strong signals. To combat this situation, Tidd et al. (2005) suggest defining a ‘search space’ to filter potential ideas, and affirm that even resource-endowed firms need to focus on a carefully selected subset of ideas identified through the development of an appropriate strategic framework. This would be guided by analysis, choice and monitoring and a balanced portfolio management strategy that transitions selected projects to the implementation phase.
The first step of the implementation phase is acquisition of appropriate knowledge and technology. This is critical for smaller firms and firms in less IACs such as in the Caribbean (ECLAC, 2012). The next step is execution of the idea in which Tidd et al. (2005) suggest a tailored and structured stage-gate approach based on Cooper (1990). A successfully executed project is now ready for launch. This step, like Cumming (1998), involves extensive preparation and testing to ensure successful absorption by the market, and a final step would be focused on review of the process toward learning (Tidd et al., 2005). However, learning is also stressed at all phases across the process and includes
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feedback into the system as supported in other models like Rothwell (1992) and Gaynor (2002).
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n Based on Tidd et al.’s (2005) model, key points that emerge
for consideration: - the need for a well-defined ‘search space’ and portfolio
management strategy and - the importance of knowledge and technology
transfer/acquisition particularly for small firms and less IACs.
Tidd et al.’s (2005) model continues the original
focus on technology with emphasis on technology transfer which is of particular importance to small firms and less industrially advanced countries. Technology acquisition provides an avenue for these entities to step into the technology frontier and operate in the 4IR. In turn, 4.0 technologies expand the ‘search space’ building on Chesbrough’s (2003) Open Innovation model and formalising the concept of the distributed network.
4.8 Assink’s (2006) Disruptive Innovation Model
Assink (2006) presents a model of innovation based on disruptive innovation as opposed to incremental innovation and focuses on large firms. It is based on the premise that large firms often fail to develop disruptive innovation. Assink (2006) describes disruptive innovation as game-changing with the potential to displace competitors and unveil new prospects for profit growth. This will become increasingly important in the 4IR which is expected to spur unprecedented transformations in the global industry and potentially alter our very existence (Schwab, 2016).
Assink’s (2006) disruptive innovation model comprises of four stages - 1) identify; 2) develop; 3) plan and 4) implement. Internal inputs include a range of endogenous factors such as resources, structure and culture while external inputs include exogenous factors from economic, social, political and competitive domains. A distinction is made with Assink’s (2006) model however, which comprises of a spiral within the four-stage quadrant structure. This spiral is formed from a series of probing, learning, decision, forward- and backward-feeding loops. These probing, learning and feedback cycles are central to Assink’s (2006) disruptive innovation model. This stresses the importance of organisational learning as a key success factor of [disruptive] innovation (Jiménez-Jiménez and Sanz-Valle, 2011).
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Based on Assink’s (2006) model, key points that emerge for consideration: - the importance of organisational learning throughout the
innovation process and - the need for continuous learning and feedback loops
throughout the innovation process.
The significance of organisational learning as a key
driver of innovation is presented in Assink’s (2006)
model. Organisational learning continues to play an important role in the context of the 4IR but represents changes in the way knowledge is acquired, transferred and utilised in the era of Big Data (Ediz, 2018). This presents a shift in the cultural orientation of firms as it relates new modalities for knowledge management. 4.9 Hansen and Birkinshaw’s (2007) Innovation
Value Chain Model
Hansen and Birkinshaw (2007) propose the innovation value chain model which consists of three sequential phases starting with idea generation proceeding to idea development and culminating with idea diffusion. The structure of the innovation value chain model is analogous to that of Ahmed (1998) and Cumming (1998). However, the innovation value chain outlines six management tasks to be undertaken across the process as – 1) internal sourcing; 2) cross-unit sourcing; 3) external sourcing; 4) selection; 5) development and 6) company- wide spread of the idea.
Cumming (1998) identifies several elements that contribute to an effective idea generation phase across various themes however, the focus of the innovation value chain model at this stage is the source of the idea. According to Hansen and Birkinshaw (2007), there needs to be a combination of internal and external sources at both micro- and macro-levels. These include intra- and inter- department levels in tandem with extra- firm and industry levels. They caution against becoming insular, particularly firms that are currently leaders of industry since history has shown that such thinking can be detrimental. Kodak is a prime example (Anthony, 2016).
At the second phase, Cumming (1998) again identifies a range of elements required. However, Hansen and Birkinshaw (2007) narrow it down to an effective combination of screening and funding mechanisms. They highlight the need for balance between these two forces since stringent funding policies can stifle novel ideas while laxed screening can lead to diversion from overall organisational strategy. At the final stage, Cumming (1998) focuses on elements related to the product and customers. However, Hansen and Birkinshw (2007) emphasise the need for buy-in of a feasible idea, not only from the end-user, but also from all sectors within the organisation in order to effectively diffuse the idea throughout the market.
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Based on Hansen and Birkinshaw’s (2007) model, key points that emerge for consideration:
- the need for consideration of internal and external factors at the idea generation phase;
the need for effective screening and funding mechanisms at the idea conversion phase, and
- need for holistic buy-in at the organisational and customer levels at the idea diffusion phase.
Hansen and Birkinshaw’s (2007) model emphasises
the need for optimal value creation along the value chain. This in an effort to make optimal use of scarce resources
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which, according to Lenart-Gansiniec, (2019), is the genesis for the 4IR. 5. Comparison amongst Innovation Process Models
There is a progression of focus across these innovation process models towards an explicit extraction of the organisational learning concept as a source of innovation. A clear path is observed starting with a focus on the individual then shifting to a focus on the process followed by consideration of culture. This progresses to a focus on the customer/end user which then proceeds to a focus on inter-firm collaboration before culminating with a focus on organisational learning and continuous feedback loops. It comes as no surprise that current models of innovation focus on organisational learning at the onset of the 4IR which is increasingly data driven.
5.1 Stages of the Innovation Process
As depicted in Table 1, the nine (9) innovation models reviewed have processes ranging from three to seven stages. All models start with some form of ‘idea generation’ and all progress to the ‘market’ stage which, for seven of the nine models, is the end of the process. However, in two models – Cooper (1990) and Tidd et al. (2005) – there is one stage beyond the market stage which entails review of the process from idea to market which is an essential step toward organisational learning. Divergent views spring from the ‘idea development/conversion’ stage. While Ahmed (1998), Cumming (1998) and Hansen and Birkinshaw (2007)
maintain a broad-based view of the ‘idea development/conversion’ stage, other models dissect the development stage into distinct phases that range from planning to manufacturing to market testing and marketing activities. Ahmed (1998), Gaynor (2002) and Tidd et al. (2005) adapt the stage-gate approach of Cooper (1990) into the respective development stage of their models.
The processes of each model represent a linear progression from one stage to the other. This holds true for Cooper (1990), Cumming (1998) and Hansen and Birkinshaw (2007), and the other models utilise feedback mechanisms at some point throughout the process. On one hand, feedback occurs at a single point in the process such as Gaynor (2002), where feedback comes at the end of the process while for Ahmed (1998), feedback occurs during the development stage. On the other hand, feedback occurs throughout various stages of the process such as Rothwell and Zegveld (1985), Tidd et al. (2005) and Assink (2006).
5.2 Contextual Themes of Innovation Process Models
Analysis of the innovation process models revealed five themes and fifty-six (56) sub-themes or factors with some recurring among the lot. Table 2 lists the various factors that emerge across the five major themes from analysis of the models reviewed. The major themes span the areas of strategy, management, organisational culture, organisational learning and communication.
Table 1. Nine Representing Models and Stages of the Innovation Process
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Table 2. Contextual Themes of Innovation Process Models
Management
Support for innovation X X X X X X
Risk tolerance X X X X X Continuous monitoring X
Control X X
Organisational culture
Innovation-oriented X X
Entrepreneurial X X X
Foster creativity X X X
Effective problem-solving X X
Worker autonomy X
Incentives/Rewards X X
Accountability X
Trust X X
Organisational learning
Throughout process X X X
Post-implementation X X
Inter-project X
Benchmarking X
Failure analysis X X
Knowledge management X X
IP generation X X
IP acquisition X X
IP protection X X
IP commercialisation X X
Communication
Intra-firm X X X X X
Inter-firm X X X X X X Gatekeepers X X
Feedback loops X X X
Appropriate channels X
Keys: X – with the contextual elements
Contextual Theme Rothwell &
Zegveld
(1985)
Cooper
(1990) Ahmed
(1998) Cumming
(1998) Gaynor
(2002) Chesbrough
(2003) Tidd et al.
(2005) Assink
(2006)
Hansen &
Birkinshaw
(2007)
Strategy
Tech-push and Need-pull X X
Inter-function
collaboration
X X X X
Efficient project execution X
Quality considerations X
Quality-Cost-Time focus X
Flexibility X X X X X
Idea champions X X X
HR development X X
Competitor analysis X
Portfolio management X
Established criteria X
Customer-centric X X X X
Market orientation, testing X X X X X X X X Pre-development activity X
Structured methodology X X X
Parallel processing X
PM approach X X
Leverage competencies X
Inter-project synergy X
Socio-technical balance X
Reduced bureaucracy X X X X Corporate philosophy X X
Enabling technology X X X X
Process innovation X
Materials development X
Capital investment X X
Multichannel funding X
Resource allocation X X X
Future-oriented X X X X X X
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All nine models reviewed considered some elements of strategy, while Rothwell and Zegveld (1985) considered factors across five themes. Management and communication factors were considered to some extent by seven models, while organisational learning factors were considered by six models and factors of organisational culture were considered across five models.
The frequency of recurrence of each factor was analysed and the factors that were considered by three or more models were identified and highlighted in bold font in Table 2. Eighteen (18) factors from a total of fifty-six factors were shortlisted based on a frequency of occurrence of three or more. A market-orientation strategy was found to be the most popular consideration among the models appearing with a frequency of eight. A future-oriented strategy, management support for innovation and inter-firm communication were the second highest recurring factors with frequency of six followed by a flexible strategy, management tolerance for risk and intra-firm communication factors with a frequency of five. Inter-functional collaboration, customer-centricity, reduced bureaucracy and enabling technology occurred four times, and all other factors had a frequency of occurrence of three. 6. Conclusion
Nowadays, most developed nations are forging at the frontiers of the 4IR, while many developing countries are trying to catch up with innovation initiatives toward sustainable development. Innovation process models have evolved and continue to change over the industrial era. These models have transformed from generations of simple linear sequential processes to generations of complex iterative parallel processes. A review of nine (9) innovation process models reveals that the innovation process does not occur in isolation but within a broader intra- and inter- organisational context.
Technology was found to be a key area of focus in several models reviewed and continues to be the driving force of innovation in the 4IR. In this vain, technology transfer was considered in one model as a means of levelling the playing field for small firms and less industrially advanced countries. There is a continued focus on customer- and market-orientation considerations. The exponential rate of change that is characteristic of the 4IR requires firms to become increasingly flexible and adaptable to these changes in customer demands and market needs which is aided by data-based 4.0 technologies that are a mainstay of the 4IR. This data-driven environment forces firms to rethink elements of organisational culture drawing on the need for increased change tolerance and enhanced organisational learning. The 4IR also promotes opportunities for innovation beyond the boundary of the firm by operating in a disrupted network where actors across the value chain work simultaneously and
independently serving to improve market response rate. This represents another cultural shift for the firm in terms of network operations.
This study focused on the stages and contextual themes governing the innovation process towards emerging industrial revolutions and organisational learning. Several enabling dimensions and elements are discussed. It explored the recurring contextual themes of nine (9) innovation process models advocated in literature, using a comparative analysis. Five contextual themes emerge from the analysis – 1) strategy; 2) management; 3) organisational culture; 4) organisational learning and 5) communication.
Within each theme, several endogenous factors were identified based on the frequency of occurrence of three or more among these models. The most commonly occurring factors, with a frequency of six or more, were found to be: from the strategy domain, customer-centric focus, market orientation and future-orientation; from the management domain, support for innovation and from the communication domain, inter-firm communication.
This study contributes to identify the contextual themes and factors of innovation process models at the firm’s level. While each model emphasised specific elements of the innovation process, all elements were found to have relevance in the 4IR with the difference being the mode of application in an increasingly digital environment.
Further studies would explore the innovation imperative with organisational and performance-influencing parameters and develop an innovation process framework in tandem with the considerations of economic growth and the global innovation landscape. Hence, emerging performance indicators, like innovation culture, cluster networks, value and knowledge creation could play a critical role in fostering innovation activities.
Comparative evaluations and case studies are suggested to examine the contextual themes and performance indicators of innovation process towards technology transfer and organisational learning in organisations. Future research could validate the elements identified for large enterprises and small and medium-sized enterprises (SMEs) of varied operations nature, across various industry sectors, separately and collectively in selected nation(s).
References:
Alam, I. (2006), “Service innovation strategy and process: a cross-national comparative analysis”, International Marketing Review, Vol.23, No.3, pp.234-254.
Allee, V. and Taug, J. (2006), “Collaboration, innovation, and value creation in a global telecom”, The Learning Organisation, Vol.13, No.6, pp.569-578,
Almeida, R. and Fernandes, A.M. (2008), “Openness and technological innovations in developing countries: evidence from firm-level surveys”, Journal of Development Studies, Vol.44, pp.701-727.
A. Koonj Beharry and K.F. Pun: Contextual Analysis of Innovation Process Models toward the Fourth Industrial Revolution
53
Anthony, S., (2016), “Kodak’s downfall wasn’t about technology”, Harvard Business Review. July 15. Retrieved from https://hbr.org/2016/07/kodaks_downfall-wasnt-about-technology?utm_campaign=HBR&utm_source=linkedin&utm_medium=social
Arias-Aranda, D., Minguela-Rata, B. and Rodriguez-Duarte, A. (2001), “Innovation and firm size: an empirical study for Spanish engineering consulting companies”, European Journal of
Innovation Management, Vol.4, No.3, pp.133-141. Assink, M. (2006), “Inhibitors of disruptive innovation capability:
a conceptual model”, European of Innovation Management, Vol.9, No.2, pp.215-233.
Avermaete, T., Via ene, J., Morgan, E.J. and Crawford, N. (2003), “Determinants of innovation in small food firms”, European
Journal of Innovation Management, Vol.6, No.1, pp8-17. Bagherinejad, J. (2006), “Cultivating technological innovations in
Middle Eastern countries: Factors affecting firms’ technological innovation behaviour in Iran”, Cross Cultural Management: An
International Journal, Vol.13, No.4, pp.361-380 Chesbrough, H. (2003), “The era of open innovation”, MIT Sloan
Management Review, Vol.44, No.3, pp.35-41. Chesbrough, H. (2011), “Everything you need to know about open
innovation”, Forbes, March 21, 2011, Accessed August 01, 2016. Retrieved from http://www.forbes.com/sites/henrychesbrough/2011/03/21/everything-you-need-to-know-about-open-innovation/#3f4c38af20b4.
Cooper, R.G. (1990), “Stage-gate systems - a new tool for managing new products”, Business Horizons, Vol.33, No.3 pp.44-54.
Crossan, M.M. and Apaaydin, M. (2010), “A multi-dimensional framework of organisation innovation: A systematic review of the literature”, Journal of Management Studies, Vol.47, No.6, pp.1154-1191.
Cumming, B.S. (1998), “Innovation overview and future challenges”, European Journal of Innovation Management, Vol.1, No.1, pp.21-29.
du Plessis, M. (2007), “The role of knowledge management in innovation”, Journal of Knowledge Management, Vol.11, No. 4, pp.20-29.
ECLAC (2012), Development Paths in the Caribbean
(LC/CAR/L.401), Economic Commission of Latin America and the Caribbean, United Nations.
Ediz, Ç. (2018), “Evaluation of Industry 4.0 from a knowledge management perspective”. In: International Congress on Politic,
Economic and Social Studies (ICPESS), No.4, Sarajevo, Bosnia and Herzegovina, Italy, May 19-22.
Eveleens, C. (2010), “Innovation management; a literature review of innovation process models and their implications”, Advisory
Council for Science, 800, 900, available at: https://www.researchgate.net/publication/265422944_Innovation_management_a_literature_review_of_innovation_process_models_and_their_implications
Garcia, R. and Calantone, R., (2002), “A critical look at technological innovation typology and innovativeness terminology: a literature review”, Journal of Product Innovation
(2006), “Antecedents and consequences of organisational innovation and organisational learning in entrepreneurship”, Industrial Management and Data Systems, Vol.105, No.1, pp.21-42.
Gassmann, O. and Enkel, E. (2004), “Towards a theory of open innovation: three core process archetypes”. Proceedings of the
R&D Management Conference, Lisbon, Portugal, July 6-9. Gaynor, G.H. (2002), Innovation by Design, AMACOM, New
York. Godin, B. (2008), “In the shadow of Schumpeter: W. Rupert
Maclaurin and the study of technological innovation”, Minerva:
A Review of Science, Learning and Policy, Vol.46, No.3, pp.343-360.
Goyal, A. and Akhilesh, K.B. (2007), “Interplay among innovativeness, cognitive intelligence, emotional intelligence and social capital of work teams”, Team Performance Management, Vol.13, No.7/8, pp.206-226.
Hansen, M. T. and Birkinshaw, J. (2007), “The innovation value chain”, Harvard Business Review, Vol.85, No.6, pp.121.
Hobday, M. (2005), “Firm-level innovation models: perspectives on research in developed and developing countries”, Technology
Analysis and Strategic Management, Vol.17, No.2, pp.121-146. Jiménez-Jiménez, D. and Sanz-Valle, R. (2011), “Innovation,
organisational learning, and performance”, Journal of Business
Research, Vol.64, pp.408-417. Kiel, D., Müller, J. M., Arnold, C., and Voigt, K. I. (2017).
“Sustainable industrial value creation: Benefits and challenges of industry 4.0”, International Journal of Innovation Management, Vol.21, No.8, 1740015.
Kline, S.J. and Rosenberg, N. (1986), “An overview of innovation”, In: Landau, R. and Rosenberg, N. (Eds.) The
Positive Sum Strategy: Harnessing Technology for Economic
Growth, National Academy Press, Washington, D.C., p.275-306. Kotsemir, M. and Meissner, D. (2013), “Conceptualising the
innovation process – trends and outlook”, Working Paper, Moscow: National Research University Higher School of Economics.
Laforet, S. and Tann, J. (2006), “Innovative characteristics of small manufacturing firms”, Journal of Small Business and Enterprise
Development, Vol.13, No.3, pp.363-380. Lee, M., Yun, J. J., Pyka, A., Won, D., Kodama, F., Schiuma, G.
and Yan, M. R. (2018), “How to respond to the fourth industrial revolution, or the second information technology revolution? Dynamic new combinations between technology, market, and society through open innovation”, Journal of Open Innovation:
Technology, Market, and Complexity, Vol.4, No.3, pp.21. Lenart-Gansiniec, R. (2019), “Organisational learning in Industry
4.0”, Problemy Zarządzania, Vol.17, No.2 (82), pp.96-108. Lin, C.Y-Y. and Chen, M.Y-C. (2007), “Does innovation lead to
performance? An empirical study of SMEs in Taiwan”, Management Research News, Vol.30, No.2, pp.115-132.
Lundvall, B-A. (1992), National Systems of Innovation: Towards a
Theory of Innovation and Interactive Learning, Frances Printer, London
Marinova D. and Phillimore J. (2003), “Innovation Models”, In: Shavinina, L.V. (Ed.). The International Handbook on
Innovation, Elsevier, p.44-53. Meissner, D. and Kotsemir, M. (2016), “Conceptualising the
innovation process towards the ‘active innovation paradigm’ – trends and outlook”, Journal of Innovation and
Naudé, W. and Szirmai, A. (2012), “The importance of manufacturing in economic development: past, present and future perspectives”, United Nations University Working Paper
Series. 2012-041, UNU-MERIT, Maastricht. Nicolov, M. and Badulescu, A.D. (2012), “Different types of
innovations modelling”, Proceedings of the 23rd International
DAAAM Symposium, Vol.23, No.1, pp.1071-1074. OECD/Eurostat (2005), Oslo Manual: Guidelines for Collecting
and Interpreting Innovation Data, 3rd Edition, The Measurement of Scientific and Technological Activities, OECD Publishing, Paris.
Oke, A., Burke, G. and Myers, A. (2007), “Innovation types and performance in growing UK SMEs”, International Journal of
Operations and Production Management, Vol.27, No.7, pp. 735-753.
A. Koonj Beharry and K.F. Pun: Contextual Analysis of Innovation Process Models toward the Fourth Industrial Revolution
54
Rothwell, R. (1992), “Successful industrial innovation: critical factors for the 1990s”, R&D Management, Vol. 22 No. 30, pp. 221-39.
Rothwell, R. (1994), “Towards the fifth-generation innovation process”, International Marketing Review, Vol.11, No.1, pp.7-31.
Rothwell, R. and Zegveld, W. (1985), Reindustrialisation and
Technology, Longman, Harlow. Salter, A., Criscuolo, P. and Ter Wal, A.L., (2014), “Coping with
Open Innovation”, California Management Review, Vol.56, No.2, pp.77-94.
Schumpeter, J.A. (1934), The Theory of Economic Development:
An Inquiry into Profits, Capital, Credit, Interest and the Business
Cycle, Translated by Redvers Opie (2008), Transaction Publishers, New Brunswick (USA) and London (UK).
Schwab, K. (2016), The Fourth Industrial Revolution, World Economic Forum.
Srivastava, S.C. (2015), “Innovating for the future: charting the innovation agenda for firms in developing countries”, Journal of
Indian Business Research, Vol.7, No.4, pp.314-320. Tidd, J. (2006), A Review of Innovation Models, Imperial College
London, p.16. Tidd, J., Besant, J., and Pavitt, K. (2005), Managing Innovation:
Integrating Technology, Market, and Organisational Change, 3rd Edition, John Wiley, New York.
Ulusoy, G. Kilic, K., Günday, G. and Alpkan, L. (2015), “A determinants of innovativeness model for manufacturing firms”. International Journal of Innovation and Regional Development, Vol.6, No.2, pp.125-158.
Van de Vrande, V., de Jong, J.P.J., Vanhaverbeke, W. and de Rochemont, M. (2009), “Open innovation in SME’s: trends,
motives and management challenges”, Technovation, Vol.29, pp.423-437.
Verloop, J. (2004), Insight in Innovation: Managing Innovation by
Understanding the Laws of Innovation, Elsevier. Zhao, F. (2005), “Exploring the synergy between entrepreneurship
and innovation”, International Journal of Entrepreneurial
Behaviour and Research, Vol.11, No.1, pp.25-41.
Authors’ Biographical Notes:
Ambika Koonj-Beharry graduated with a BSc. and an MPhil in
Industrial Engineering from The University of the West Indies
(UWI), St. Augustine, Trinidad and Tobago. She is presently an
instructor and pursuing her PhD in Industrial Engineering at the
UWI-Department of Mechanical and Manufacturing Engineering.
Her research interests are in the fields of knowledge management,
cluster development and innovation.
Kit Fai Pun is Chair Professor of Industrial Engineering (IE) and
the coordinator of IE Research Group at The University of the
West Indies (UWI), St Augustine, Trinidad and Tobago. He is
Chartered Engineer in the UK, and Registered Professional
Engineer in Australia, Europe, Hong Kong, and The Republic of
Trinidad and Tobago. Professor Pun is presently the Chair of the
Technology and Engineering Management Society Chapter of the
IEEE Trinidad and Tobago Section. His research activities include
industrial and systems engineering, engineering management,
quality management, performance measurement, and innovation
systems.
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