QUALITY CONTROL SYSTEM FOR TUCKSIN ENGINEERING SDN. BHD.

A PROJECT REPORT

Submitted by

NELSON DAVID BASSEY (I14005232)

ZIM CHIDERA EZEVILLO (I12002112)

EKO PRATAMA

DANNY GOH SHIN TECK

NWAFOR IKECHUKWU

In partial fulfillment of the award of the degree

Of

BACHELOR OF ENGINEERING

In

MECHANICAL ENGINEERING

FACULTY OF SCIENCE, TECHNOLOGY, ENGINEERING AND MATHEMATICS

INTI INTERNATIONAL UNIVERSITY, NILAI

NOVEMBER 2015

QUALITY CONTROL SYSTEM FOR TCKSIN ENGINEERING SDN. BHD.

Abstract

Over the years, technological advancements have ensured that businesses have had to evolve

to be more efficient in terms of productivity and client satisfaction. Quality control has

become a very important tool in measuring and improving the performance of a company.

TSG has made a name for itself as a manufacturing company that meets the needs of its

clients in a timely and efficient manner.

For this project, we have used the Total Quality Management (TQM) method. This method is

an adaptation of the Statistical Quality Control (SQC), which was created by Fredrick W.

Taylor in his book titled Principles of Scientific Management. The use of this method can be

traced back the mid 1920’s at the Western Electric plant of the Bell system. The current

variations of the TQM currently in use were created by Edward Deming and Joseph Juran.

This project focuses on creating a system based on TQM for TSG to use to measure and

adequately control quality in their manufacturing process. We have decided to focus only in

two of the services that are rendered by the company which are Design and Fabrication. We

have based our system on five areas of Measurement: Fabrication process measurement, Key

Design Performance areas, Compliance measurement, Efficiency Management, Design

Process Measurement.

This design project will last for the duration of fourteen weeks (one semester). This is a group

project, and we must work together to complete the tasks. Time management, team

management, and good planning are part of the learning outcomes of this project.

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ACKNOWLEDGEMENTS

As a token of gratitude to all who directly and indirectly contributed to the success of

this project, we would like to thank the following people.

We would like to express our special thanks to Tucksin Engineering Sdn. Bhd. as well

as Mr. Gerald Victor for giving us the opportunity to do this wonderful project and also for

giving us his years of experience and expertise in simple advises towards our project.

Thanks to our fellow colleagues who assisted us with transportation and other

logistics in support of our project work. Thank you and God bless you.

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STUDENT’S DECLARATION

We declare that this project report titled “QUALITY CONTROL SYSTEM FOR TUCKSIN ENGINEERING SDN. BHD.” is the result of our own study except as cited in the references. The report has not been accepted for any degree program and is not concurrently submitted in candidature of any other degree program.

Signature of Group Leader: ____________________________

Group Leader’s Name: Eko Pratama

Date: November, 2015

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TABLE OF CONTENTS

Page

ABSTRACT i

ACKNOWLEDGEMENT ii

DECLARATION iii

TABLE OF CONTENTS iv

CHAPTER 1: INTRODUCTION

1.1 Project background 6

1.2 Project statement 6

1.3 Objective of project 6

1.4 Project scope 7

1.5 Research overview 7

CHAPTER 2: LITERATURE REVIEW

2.1 Introduction 9

2.2 FMEA 9

2.3 QMS 11

CHAPTER 3: PRODUCT (INTIMaP 1.0 Beta)

3.1 Product background 15

3.2 Product objectives 15

3.3 The Five areas of measurement 15

3.4 Analysis and Measurement 17

CHAPTER 4: RESULT AND DISCUSSION

4.1 TQM Cycle 24

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3.1 CHAPTER 5: CONCLUSION AND RECOMMENDATION

5.1 Conclusions 27

5.2 Recommendation 27

REFERENCES

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CHAPTER 1

INTRODUCTION

1.1 Project Background

Tucksin Engineering is a company headquartered in Malaysia that provides a a full

cycle of design, detailing, fabrication and erection services. The company was

established in 1986 and their area of expertise has expanded to various scopes of

steelworks in industrial and commercial structures.

The current quality measurement process utilized by TSG does not involve the use of

statistical data and an analytical approach. The current method in use by the company is

based on a trial by error approach, which is neither accurate nor precise. This method places a

significant drawback on effectiveness and reliability of output. Our system provides an

avenue for effective data collection and analysis for quality measurement of the entire

manufacturing process at TSG.

1.2 Project Statement

In line with the TSG vision to further establish itself as an approved global supplier in the

various retail industries where it has formed strategic partnerships, this project aims to

develop a Quality Measurement System for the effective measurement and management of

TSG’s manufacturing processes.

1.3 Objective of project

In accomplishing the aim stated above, the primary objectives are as follows:

Design a system to improve the quality of the entire manufacturing process

Perform a test to show how to carry out analysis

Perform a Failure Mode Effect analysis to what corrective measures can be taken

using some common problems that occur in the manufacturing process

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1.4 Project Scope

From the project title that has been chosen, the development of this project must

include representation of the process methodology in free-body diagram and process flow

diagrams. Secondly, a data sheet or specification for following the chosen methodology shall

be included. There is however some guide that must be followed in order to complete this

project.

1.4.1 Literature Review: We researched information from expert inquiry, texts and from

the internet that is related to our project. They include:

i. Quality Measurement systems that are already in use today.

ii. Important factors that affect the quality of the Manufacturing Process.

iii. Research on Total Quality Management (TQM)

1.4.2 Primary Design/Analysis:

i. Created a spreadsheet to enable data entry

ii. Carried out analysis on the results from the data entry using several

statistical tools such as Mean, Range and Standard Deviation.

iii. Performed an FMEA analysis based on our analysis to show the

corrective measures that can be used based on the results that are gotten

from the analysis.

1.4.3 Prototype Fabrication:

a. Materials used:

i. Microsoft Excel

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1.4.4 Report Writing:

i. Progress report was written from the initiation of the work process until

the completion of the project.

ii.

1.5 Project Overview

The following materials and tools were used in the project:

Microsoft Excel

In our world today, quality control is an aspect of business that has proven to be

invaluable in improving the performance of a company. Quality control is an evaluation that

is needed for corrective responses. Most manufacturers would never think of eliminating the

quality control system from their production processes. Without quality control, the number

of defective products that must be reworked, scrapped or returned would dramatically

increase.

Quality Control helps to regulate and create consistency in products and services,

therefore attracting more clients to a business. It provides a useful tool to judge the

performance of a company in terms of its customer base. In this report, a relationship

between satisfied customers and dissatisfied customers in terms of loyalty will be shown. A

good quality control system helps create an edge in our competitive world while also being

profitable as a result of an increase in sales.

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CHAPTER 2

LITERATURE REVIEW

2.1 Introduction

Tuck Sin Engineering Sdn. Bhd. have been in the manufacturing industry for several

years. However up till now, there has not been any system for measuring and

controlling quality within the manufacturing process. So far, they have largely

depended on detecting and fixing issues using a trial by error method. We were

invited to develop a Quality Control System for the company. For our design, we have

chosen to use the TQM (Total Quality Management) method.

2.2 FMEA

Introduction and History

Also called: potential failure modes and effects analysis; failure modes, effects and criticality analysis (FMECA).

Failure modes and effects analysis (FMEA) is a step-by-step approach for identifying all possible failures in a design, a manufacturing or assembly process, or a product or service.

“Failure modes” means the ways, or modes, in which something might fail. Failures are any errors or defects, especially ones that affect the customer, and can be potential or actual.

“Effects analysis” refers to studying the consequences of those failures.

Failures are prioritized according to how serious their consequences are, how frequently they occur and how easily they can be detected. The purpose of the FMEA is to take actions to eliminate or reduce failures, starting with the highest-priority ones.

Failure modes and effects analysis also documents current knowledge and actions about the risks of failures, for use in continuous improvement. FMEA is used during design to prevent failures. Later it’s used for control, before and during ongoing operation of the process. Ideally, FMEA begins during the earliest conceptual stages of design and continues throughout the life of the product or service.

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Begun in the 1940s by the U.S. military, FMEA was further developed by the aerospace and automotive industries. Several industries maintain formal FMEA standards.

What follows is an overview and reference. Before undertaking an FMEA process, learn more about standards and specific methods in your organization and industry through other references and training.

FMEA is a qualitative and systematic tool, usually created within a spreadsheet, to help practitioners anticipate what might go wrong with a product or process. In addition to identifying how a product or process might fail and the effects of that failure, FMEA also helps find the possible causes of failures and the likelihood of failures being detected before occurrence.

Type of FMEA

There are a variety of FMEA; some are used much more often than others. The type of FMEA’s currently in use are:

System - focuses on global system functions Design - focuses on components and subsystems Process - focuses on manufacturing and assembly processes Service - focuses on service functions Software - focuses on software functions

Why Use FMEA ?

FMEA is designed to assist the engineer improve the quality and reliability of design. Properly used the FMEA provides the engineer several benefits. Among others, these benefits include:

Improve product/process reliability and quality Increase customer satisfaction Early identification and elimination of potential product/process failure modes Prioritize product/process deficiencies Capture engineering/organization knowledge Emphasizes problem prevention Documents risk and actions taken to reduce risk Provide focus for improved testing and development Minimizes late changes and associated cost Catalyst for teamwork and idea exchange between functions

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When to Use FMEA

When a process, product or service is being designed or redesigned, after quality function deployment.

When an existing process, product or services is being applied in a new way.

Before developing control plans for a new or modified process

When improvement goals are planned for an existing process, product or service.

When analyzing failures of an existing process, product or services.

Periodically throughout the life of the process, product or service.

2.2 Quality Measurement System Importance

QMS is a quality management system is a management technique used to

communicate to employees what is required to produce the desired quality of products and

services and to influence employee actions to complete tasks according to the quality

specifications. The purpose of the Quality Measurement and Analysis is to develop and

sustain a measurement capability used to support management.

With QMS, the company is able to satisfy the customer by achieving or exceeding the

specifications set by the customer. Furthermore QMS is also able to fulfill the organization`s

requirements both internally and externally, and at an optimum cost with efficient use of the

available resources.

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2.2.1 Quality Measurement System Benefits

Figure 1 shows how QMS benefits the company in term of saving time. Before 1996

Numetric Manufacturing Company needs more than 107 weeks to complete the 6 phases of

duration improvement, but by adapting the quality control system, the company can reduce

the duration of the 6 phase, 37 % , to 24,5 weeks just in 3 Years. From this case it is proven

that QMS is giving a positive impact in term of time efficiency

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Figure 2, Second chart above shows that the pink dot is in the low capacity and low

productivity region, and the green dot is in the region of high capacity and productivity. And

the pink color point is when they are lack of regular quality measurement data. The green dot

is when they are adapting the QMS. By this chart we can see that when the company have a

good quality data measurement, they can improve and optimized the capacity and the

productivity of the company.

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Here are some points what are the Benefits of regular Quality Control and Measurement:

- It pushes the company to improve the quality level of their workmanship because of the

pressure of inspections and non-acceptance

- It forces your suppliers to meet your order terms and product requirement, or to compensate

you for any discrepancy ( exact materials, colors, aspect, packing , functions..)

- You don’t discover quality problems after the goods delivered.

- You have the time to adapt your planning and take decisions

- The factory can rework the goods itself and will be more careful in future.

There are some big risks for the company itself if they are lack of quality control and

measurement:

- The shipment cannot be sold at all (too many visual defect, wrong size, dangerous, etc.)

- Products have to be sorted out and reworked in the importing country, at great cost to the

importer.

-The company image suffers because of poor quality delivered to customers

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CHAPTER 3

PRODUCT (INTIMaP 1.0 Beta)

3.1 Product Background

INTIMaP 1.0 is an excel spreadsheet, with tables and formula with makes for a simple

software. The excel platform make it possible for data entry and result/analysis

generation. The system comprises 28 independent parameters across the 5 main areas of

design and fabrication operations.

The current Beta version contains 13 analysis graphs which consists of pie charts, bar

charts, line graphs and histograms for selected parameters. Over time more parameters,

analysis and graphs can be added/plotted as the scope increases, to enhance better process

quality management.

3.2 Product Objectives

i. Generate data on design process

ii. Quantify and qualify errors, needs, areas of concerns and “what should be fixed”

iii. Make easier the assessment of quality problems and root causes.

iv. Enable tracking of impact of changes and corrections in design process.

3.3 The five (5) Areas of Measurement

i. Design process measurement:

This table measures the general operational flow of the design process. The

parameters considered includes the size of projects, clarity of requirements given

by client/customer, lead time (forecasted period for design process to be

completed), the cycle time (actual duration taken for the design to be completed

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including the recalling time), number of errors noticed in the design, errors fixed

after first review process, and the delay time.

ii. Efficiency Management

This table contains parameters which measure how much output is being produced

over a period of time, taking into consideration the number of engineers and hours

put into project. This is also known as “Throughput”. Overall design process

effectiveness has also been considered. The parameters contained in this table

includes: size of project, number of delays on project, causes of delay (qualitative

data measurement), man-hours put into project, number of manufacture rejects

and number of engineers working on project.

iii. Compliance Measurement

A measure of the number of times a design was done outside the guidelines of

normal regulatory compliance rules or requirements by the client and

production/manufacturing plant. These non-compliances need to be fully

documented as to the specific non-compliance time, reasons, and resolutions. The

parameters included in this table include, size of project, reportable naming

corrections in design, reportable miscommunication and stage noticed/reported.

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iv. Key Design Performance Areas

This table contains measures the capability of the design process and engineers

with respect to the overall goals and objectives of the company. Other factors

considered are innovation and out-sources designs and processes.

v. Fabrication Process measurement

This table contains parameters measured over time. With sufficient data, trends

are plotted as a reliable indicator for growth, innovation, and improvement of the

general quality of the company’s product and services.

3.4 Analysis and Results

Using arbitrary data, the following analysis were performed and the graphs plotted.

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3.4.1 Project Distribution by Size:

The Figure below shows both the frequency and percentage project distribution by

size. 3 of all projects handled by the company are major projects, a number which is

equal to that of medium sized projects. From the analysis, only 25% of the company’s

design projects are big projects.

The following table shows the data from the bar graph above was plotted:

3.4.2 Project Distribution by Complexity

The figure below shows the distribution of projects according to level of complexity.

The three levels of complexity are high, medium and low. High level of complexity

requires specialized skills and expertise to perform, while low complexity projects do

not require specialized knowledge and can be performed by an amateur engineer.

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The figure indicates that 4 projects were of high complexity, with 3 of those being

major projects, and 1 a medium sized project. This makes for 75% of high complexity

projects, major projects. None of the projects handled by the company are of low

complexity; therefore by analysis this company should have more skilled design

engineers to maintain quality in its design processes.

3.4.3 Clarity of Requirements by Project Size and Complexity

The table below shows how clear the requirements were for each project. A clear and

detailed requirement will lead to a better design quality, lesser errors and almost zero

delay time. However, a confusing requirement increases on cycle time, errors and

cost.

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From the table above, only 1 highly complex project had clear and detailed

requirement, with 1 confusing requirement. 4 not to complex projects were slightly

clear. By project size, 0 major projects had clear and detailed requirements, with 1

major projects having confusing requirement. According to the data available, this is a

recipe for poor quality output and increased cycle time.

3.4.4 Timeliness and Efficiency of design process

The timeliness of a project is very important to a company. A failure to deliver in due

time can cost the company a fortune, and eventually lose the client or customer.

Paying attention to the graph above is paramount.

This graph shows the deviation of the cycle time from the lead time which indicates

delay time in project. The goal of the quality management process is to reduce this

divergence as much as possible. This can be achieved when the number of errors are

reduced in the design process, and to achieve this, the other graphs would be a great

resource.

3.4.5 Problem-Skill Gap Measure

Understanding the number of errors detected in the designs, when they were returned

to be fixed, and how many were fixed is a good indicator of the competence of the

engineers working on the project. The following line graph shows this information.

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The goal of the design engineers is to match both the number of errors detected with

the number of errors fixed, in the shortest possible time. From the data and result

above, there is a problem-skill gap, however not very much. The wider the gap, the

more critical the conditions. This can be observed from project 2. The gap between

the errors detected and those fixed opened, and the delay time increased significantly.

3.4.6 Trends in Fabrication Process

i. Rejects over time

The line graph above indicates the trends of rejects by the months of the year.

As shown, the months of July and February recorded the highest number of

rejects. The goal of the company is to reduce number over time.

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Over a longer period of time, the progress of the company can be measured.

The bar chart above shows that the company isn’t improving on its effort to

eliminate the number of rejects. A rising trend is noticed.

ii. Defects Missed per Project over time

However, there is no noticeable trend in the bar chart below; the company is

not getting better in detecting defects. The goal is to see a downward trend

over the period of a year. This is definitely a watch list for to company.

iii. Acquired projects over time

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The ultimate measure of a company’s growth can be the number of customers

and/or projects it acquires over a defined period of time. Using 11 years as a

measure, the company hasn’t recorded any upward growth in the number of

projects it has acquired.

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CHAPTER 4

RESULTS AND DISCUSSION

4.1 TQM (TOTAL QUALITY MANAGEMENT)

TQM Cycle

We have developed a quality measurement system using the TQM method which is widely

recognized and has been used by several companies around the world. It is a cycle for

continuous improvement. The cycle begins with the Data collection stage during which the

company makes use of the spreadsheet that we have designed. After this comes the Data

analysis which is done using several statistical tools such as Mean, Range and Standard

deviation. The next stage is the corrective measures stage during which the company

implements changes based on the results gathered from the analysis. Finally, the company

takes a look at the manufacturing process to see if the changes that were implemented have

yielded good results and the cycle repeats itself.

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Data collection

Data analysis

Corrective Measures

Implemented

Check TQM MODEL

Procedure for the FMEA Analysis

1.) Form a team of people with a wide variety of knowledge about the process, product or service and customer needs according to the Process Step that is being analyzed.These functions included are:

- Design

- Manufacturing

- Maintenance

- Purchasing

- Marketing

- Customer service

2) Identify the scope of the FMEA (Concept, System, Design, Process or Service )

3) Fill in the Failure Modes Analysis Effect (FMEA) form.

4) Identify the functions of the scope. For instance, questions like " What is the purpose of this system, design, process or Service? What are the expectations of our customers? "

5.) For each function, identify all the ways failure could happen. These are all potential failure modes.

6.) For each failure mode, find out the effects of the failure mode if it is not prevented.

7.) Rate how serious each effect is by giving it a rating. Severity, S is rated on a scale from 1 to 10 where 1 being insignificant and 10 most severe.

8) For each failure mode, determine all the potential root causes.

9) For each cause, determine the Occurrence rating, O. This rating estimates the probability of failure occurring for that reason during the lifetime of the scope. Occurrence is rated on a

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scale from 1 to 10 where 1 is extremely unlikely and 10 is inevitable.

10.) For each cause, identify the current process controls. These may be test, mechanisms, procedures and so on that you now have in place to keep such failures from reaching the customer beforehand. These controls might detect the failure and prevent the cause from happening.

11.) For each process controls, determine the Detection rating , D. This rating estimates how well the controls can detect either the caus or its failure mode after they have occur but before the customer is affected. Detection is rated on a scale from 1 to 10, where 1 means the control is absolutely certain to detect the problem and 10 means the control is most absolute not to detect the problem.

12.) Calculate the Risk Priority Number ( RPM ) which equals S x O x D.

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CHAPTER 5

CONCLUSION AND RECOMMENDATION

5.1 Conclusions

During our several visits to Tuck sin Engineering, we noticed a lack of statistical data to track

the growth of the company while also increasing the quality of the manufacturing process.

The design of this Quality Control System eliminates the dependence on the trial by error

approach, which is currently in use at TSG. Using our system, we are able to analyze the

performance level of the company in several key areas in order to enhance the productivity of

the company.

Our design still has several areas where it can be improved. It can be modified to measure

and analyze a much wider range of data thus further improving the quality and productivity

of the company. There are several software currently available in the market, which provide a

means of onsite data collection and analysis for manufacturing companies, but these software

come at a very high cost. The advantage our design has over such software is that it comes at

a very low cost and requires just a basic knowledge of statistical data analysis.

5.2 Recommendation/Next Steps

The design can be further improved to measure more areas of the manufacturing process.

In the current setup at TSG, they carry out work on Design, Fabrication, Detailing and

Erection services. Currently, our design only concentrates on design and fabrication.

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REFERENCES

1) http://www.tatasteelconstruction.com/en/reference/teaching-resources/

architectural-teaching-resource/technology/fabrication-and-erection-of-steelwork/

inspection-and-quality-control

2) https://www.google.com/url?

sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&uact=8&ved=0CCIQFjA

BahUKEwiwr_nRxurIAhUDkJQKHe7RDw8&url=http%3A%2F

%2Fwww.tl9000.org%2Fregistration%2Fdocuments

%2FDesign_Process_Measurement_System_Guidance_Rev_2_1.pdf&usg=AFQj

CNGyc3HFuHSip00qmuhdUSaiOhC5kQ&sig2=Gl8DG-

3) https://www.google.com/url?

sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&uact=8&ved=0CCsQFjA

BahUKEwi2_Kn6xurIAhWBk5QKHfGaBcM&url=http%3A%2F

%2Fcife.stanford.edu%2Fsites%2Fdefault%2Ffiles

%2FWP124.pdf&usg=AFQjCNHm22Xvyw6T__ F-

EWqSzTKUDgkOUg&sig2=GLprhHSpaRRNtyEP4hrEMA&bvm=bv.106379543

,d.dGo

4) http://www.isixsigma.com/tools-templates/fmea/quick-guide-failure-mode-and- effects-analysis/

5) http://asq.org/learn-about-quality/process-analysis-tools/overview/fmea.html 6) http://www.npd-solutions.com/fmea.html 7) http://webdb.ucs.ed.ac.uk/operations/honsqm/articles/fmea.pdf 8) http://www.geocities.jp/takaro_u/fmea_eng.html

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