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Quality Improvement in D’Vinia’s Buko Pie
Through Reduction of Burnt Pie Crust Dangue, Ruth Esther1, Lijauco, Irene Isabella2, Manalo, Renzo Robert3
Department of Industrial Engineering, University of the Philippines – Los Baños
Los Baños, Laguna, Philippines [email protected]
Abstract – This study utilizes statistical analysis and quality
control tools to investigate the recurrence of burnt pie crust in the
daily batch production of special buko pie in D’Vinia’s Buko Pie
and Food Products. Following the analysis, the mitigation of the
quality problem can be sought by purchasing new ovens, laying
out a maintenance schedule for the ovens and modifying aspects
related to baking.
I. INTRODUCTION
A. Company Background
D’Vinia’s Buko Pie and Food Products is a family-owned
bakeshop founded during 1990 by Divinia Baclig and Emma
Baclig. The business started by renting a stall, formerly owned
by Mr. Tito Barreto, in Bucal, Calamba, Laguna. By 1991, the
occupants decided to buy another available stall in Pansol,
Calamba, Laguna which became the location of their main
branch. D’Vinia’s was formally established during the same
year and is currently a registered food producing unit [1].
Fig.1.Logo of D’Vinia’s Buko Pie and Food Products [1]
At present, there are two outlets of D’Vinia’s Buko Pie and
Food Products: the main branch and a second outlet which
happens to be situated on Bucal. Apart from Divinia Baclig,
there are fourteen (14) employees currently working in the
bakeshop. D’Vinia’s mainly produce buko pies as well as other
products such as cassava cakes, ube macapuno pies, buko tarts,
pineapple cake, espasol and sapin-sapin. Most of its materials
are sourced from Prime PBS Bakery Supply, MWC Enterprise
and local vendors of coconut meat.
D’Vinia’s is currently a supplier of buko pies in a
cooperative situated in Enchanted Kingdom (EK), an
amusement park in Sta. Rosa, Laguna. In addition, buko pies
are also delivered to some allied peddlers outside EK and
around Mayapa Bus Terminal.
B. Background and Significance of the Study
With the onset of a stable business operation in D’Vinia’s
Buko Pie and Food Products, the management noted in a
personal interview that the quality of their goods has to be
consistently in par with their customers’ expectation as to
sustain leverage on today’s market. However, it proves to be
difficult as the business is continually facing some problems
that risk the level of quality of their products.
The recurring incidence of baked pies with slightly burnt
crust is one of the quality problems that D’Vinia’s is recently
encountering. During the same interview, the management has
pointed that the special buko pie, having the greatest profit
contribution to the business, dates the most number of
occurrences of burnt crust. The sales account, however, is kept
in confidence thus no numerical value can be affixed with the
profit contribution in the past accounting period.
The identified problem has resulted to special buko pies
being reworked by scraping the burnt region. In consequence,
the buko pie decreases in size and is sold at PhP120. This marks
sales opportunity loss amounting to PhP80 per reworked pie
sold.
Data collected in the last three weeks (see Appendix A)
show that the daily production of special buko pies averages
two to three batches each day, with each batch amounting to 45
pies. The expected number of special buko pie with burnt crust
is 23.28 per cent of the total inspected, or approximately 23 pies
reworked on a day-to-day basis.
(i)
(ii)
Fig.2.Graphical summary of inspected special buko pies
from (i) oven A and (ii) oven B
Projecting operation on annual timeline, the business would
accumulate significant amount of losses on their sales revenue,
approximately equivalent to PhP671, 600 which is 10.13 per
cent of the expected annual revenue for the sale of special buko
pies. To some extent, this also results to the gradual decrease of
their customer base.
The study is intended to effect improvement in the quality
of D’Vinia’s buko pie products through reduction of burnt pie
crusts using statistical process control tools. This involves
systematic identification and analysis of the factors which lead
to the problem presented. The management stated that the
workers’ performance level and the working condition of the
ovens dictate whether the baked pie would have slightly burnt
patches. Employing quality control measures will address this
incident, reducing the percentage of buko pies baked with
defects per batch on a daily production and potentially, gaining
hard savings and positive customer appraisal.
C. Statement of the Problem
The recurrence of baked special buko pies with burnt pie
crust, with weighted average equivalent to 23 pies per daily
production, has cost D’Vinia’s Buko Pie and Food Products
opportunity loss of PhP671, 600 which is about one tenth of the
expected annual revenue of the business, and to some extent,
weakened its leverage on the food industry.
D. Objectives of the Study
The study aims to effect quality improvement in the
production of special buko pies in D’Vinia’s Buko Pie and
Food Products, specifically;
To reduce the proportion of special buko pies with
burnt crust to 11.65 per cent, marking a 49.96 per cent
down shift in the proportion defective per daily
production
To level the capability of the shop’s baking ovens in
the production of non-defective buko pies
E. Scope and Limitations
The study focuses only on quality improvement of special buko
pies, exclusive of those delivered to Enchanted Kingdom.
Moreover, the study is only interested in reducing the number
of pies with burnt crust, not with other dimensions of food
quality. Most importantly, the study assumes the following to
simplify the system under study:
o The management has a strict policy that upon inspection of
special buko pies, those classified as defective are
reworked instantaneously.
o All baked special buko pies, even those reworked, are sold
at the end of the day
F. Date and Place of the Study
The study takes place in D’Vinia’s main branch located in
Pansol, Calamba, Laguna from September to November 2014.
Fig.3.Location of D’Vinia’s Buko Pie and Food Products (Google Maps)
G. Roadmap/Milestone
Fig.4 shows the schedule for the activities performed during
the conduct of the study.
34
135
Withburntcrust
Withoutburntcrust
39
92
Withburntcrust
Withoutburntcrust
Fig.4.Gantt chart for study conducted
II. METHODOLOGY
A. Procedures
After seeking approval from D’Vinia’s as the company of
interest for the study, a one-week familiarization of how the
business operates is conducted. Through an interview with
Divinia Baclig, the common quality problems encountered by
the business are identified, however, the study narrows its
scope to the reduction of the number of pies with burnt crust.
Also, historical data on production level, sales and incidence
rate of the quality defect are asked. However, with the absence
of past records, the figures are experience-based estimates
provided through correspondence with the management.
The data are gathered every weekend on their main branch
in Pansol. The floor layout of the area where the special buko
pies are baked is drawn. With each batch of pies produced, the
number of pies with burnt pie crust is noted according to a set
metric.
The data collected are further analyzed. To identify the root
causes of the problem identified, an Ishikawa diagram is
constructed. The root causes are then classified whether they
are controllable, non-controllable and experimental. Statistical
analysis is employed to investigate whether there are assignable
causes of variability in the company’s production.
Based on the conclusions drawn from the analysis,
corrective measures are recommended to address the current
situation of the company. Areas for further study are elaborated
to give leeway to improvement of the experimental design.
B. Definition of Terms and Symbols
To better understand the underlying concepts, the following
terms and symbols are defined in the following table.
TABLE I
DEFINITION OF TERMS
Term Definition
Binomial capability
analysis
Analysis tool used to generate process
capability reports for attribute data that
follow the binomial distribution [2]
Capital investment Money invested in a business with the
expectation to gain profit [3]
Cash flow The amount of cash generated and used by a
company in a given period [4]
Controllable factor
Existing parameter in a system that can be
adjusted usually with an acceptable impact
on cost [5]
Cumulative
percentage
Percentage of the cumulative frequency
within each interval; expresses frequency
distribution [6]
Defective
A product that has one or more
nonconforming quality characteristics to its
specification
Experimental factor
Factor with no current solution and is
gradually resolved through the formulation of
trials
Factor rating
Method that evaluates alternatives based on
comparison after establishing a composite
value for each alternative [7]
Flow diagram Tool used to illustrate the movement of men,
materials, etc. in a given process [8]
FPC
Tool that defines and documents changes in a
process through the use of symbols
representing different types of activities [8]
Gantt chart
Tool that visually outlines the tasks involved
in a project and their order shown against a
timescale [9]
Hypothesis
An assumption about certain characteristics
of a population or probabilistic mechanism to
be tested using the generated observations
[10,11]
Ishikawa diagram
Diagram that identifies potential factors
causing an overall effect by analyzing
sources of variations from man, method,
machine, material, management, and
environment [12]
Job description
A detailed overview of what a given job is,
what it is about and how it is supposed to be
done [13]
MARR
Minimum attractive rate of return; the
reasonable rate of return to be met for an
alternative to be economically viable [14]
Non-controllable
factor
A source of variability, either internal or
external to the system that may either be
unchangeable or too costly to alter [15]
OPC
A tool used to shows an entire process along
with the points at which materials are
introduced, the sequence of inspections, and
all operations not involved in material
handling [16]
Opportunity loss
The payoff difference incurred from giving
up an alternative to achieve something else
[17,18]
p-chart
Attributes control chart used to measure the
stability of data collected in subgroups of
varying sizes; shows a proportion on
nonconforming items rather than the actual
count [19]
Present worth Present day value of an amount that is
received at a future date [20]
Production
The creation and distribution of goods to
consumers, aimed to satisfy human wants
[21]
Proportion defective
The ratio of the number of nonconforming
items in a given population to the total
number of items in that population [22]
Revenue
Total amount of money that a company gains
through its business activities, exclusive of
deductions such as costs and discounts [23]
Rework
The modification of a defective or non-
conforming item during or after inspection
[24]
Salvage value
The estimated value each asset will have
after it is no longer going to be used in the
operation of a business [25]
Stability
Total variation in the measurements obtained
with a measurement system on the same
master or parts when measuring a single
characteristic over an extended time period.
TABLE II
DEFINITION OF SYMBOLS [26]
Symbol Term Description
Operation
A main step
wherein a part,
product or material
is transformed
Inspection
Indicates
examination or
checking for quality
or quantity
Storage
Controlled storage
in which material is
received into or
issued from a store,
or an item is
Transport
The movement of
workers, materials
or equipment
Delay/Temporary
storage
Indicates a delay in
the process or an
object set aside
until it is required
III. SYSTEMS DOCUMENTATION
A. General Processes of the Company
D’Vinia’s produces various pastry products such as buko
pies cassava cakes, ube macapuno pies, buko tarts, pineapple
cake, espasol, and sapin-sapin. The table below shows the price
for each product.
TABLE III
PRICE LIST
Item
No. Product Name
Price
(in PhP)
1 Buko Pie 200
2 Buko Tart 200
3 Cassava Cake 180
4 Espasol 80
5 Pineapple Pie 180
6 Sapin-sapin 150
7 Ube Macapuno Pie 220
All of these products are baked in a single production area.
Hence, the management schedules the baking of each product,
accounting the demand of the customer. The flow diagram (see
Appendix B) illustrates the flow of production within the
vicinity.
Currently, there are fourteen (14) employees working in the
bakeshop. Below is a list showing the job descriptions and the
number of employees delegated to each task.
TABLE IV
JOB LIST
Job
No. Description
Number of
employees
1 Sell product, assist customers 2
2 Bake pies, tarts, etc. 8
3 Manage product delivery 2
4 Manage financial records and
accountabilities during fiscal period 2
In contract with the cooperative, D’Vinia’s is able to market
its products in Enchanted Kingdom. The park, by which a
significant number of people visit in, provides D’Vinia’s the
strategic advantage to gaining an expansive range of potential
customers. The management noted, however, that only 70 per
cent of the total sales go to the business in accordance with the
signed agreement.
B. Subject under Study
Given the wide range of products offered by D’Vinia’s, the
study would limit its scope to the production of special buko
pies with the objectives as stated above.
Mentioned during the interview with Divinia Baclig are the
suppliers of the raw materials for baking special buko pies. The
manager affixed an estimated cost of purchasing each
ingredient and material, some expressed in bulk.
TABLE V
SUPPLIER OF RAW MATERIALS
Item Supplier Cost
(in PhP)
Box MWC Enterprise 890/batch
Flour
Prime PBS Bakery Supply
1000/sack
Sugar 2150/sack
Baking
powder 1180/bag
Lard 2000/40-kg
Coconut
meat Local suppliers 90-105/kg
Milk N/A 7500/25-kg
To illustrate how the baking process simulates, attached are
the operations process chart (OPC) and flow process chart
(FPC).
The OPC (see Appendix C) provides the chronology of the
operations and inspections performed in the production of
special buko pies. It shows the materials used and the time
taken by worker to carry out the action. However, this does not
explicate the material handling and storage of the buko pies.
The FPC (see Appendix D), on the other hand, contains a
more detailed account of baking special buko pies which
includes the main operation, transferring of materials, possible
delays in production, inspection, and storage time. From the
FPC, the interest of the study covers the time that the product
is transferred from the production area to its final inspection.
The management stated that the preparation of raw materials
is the first step to production. The next process is the
preparation of the filling and the dough. After which, the pie is
prepared by laying a mantle of dough on the mold, followed by
the filling and topped with a layer of dough. The pies are placed
on the oven for approximately 30 minutes. The pies are
disembarked from the oven, ready for inspection and delivery
to satellite stores.
IV. RESULTS AND DISCUSSION
A. Problem Identification
The main problem observed in the firm is its production of
buko pies with burnt crusts. The difference between the
defective and non-defective pies are presented in the figure
below.
(a) (b)
Fig.5. The buko pies that are (a) non-defective, and (b) have burnt crust.
Buko pies are considered good if they have evenly golden
crusts, however for this study, if one-eighth or more of a pie’s
crust is burnt as shown above, it is considered defective and is
thus reworked.
Using this measure, samples were gathered and hypothesis
testing is first conducted in order to determine whether the
proportion defective in machine 1 is statistically equivalent to
that in machine 2. Setting the level of significance at 5%, the
hypotheses to be considered in the test are as follows:
Ho The expected proportion defective in machine 1 is
equal to that of machine 2 (P1 = P2).
Ha The expected proportion defective in machine 1 is
not equal to that of machine 2 (P1 ≠ P2).
Using the summarized data, the test result for the test of two
proportions is shown below.
Fig.6. Result from test and CI for machine 1 and machine 2 in Minitab.
Since p-value is equal to 0.056, which is greater than the set
α=0.05, we therefore fail to reject Ho, meaning it can be
concluded that the proportion defective obtained from machine
1 is statistically equivalent to that of machine 2. This being
established, it would also mean that it is necessary to consider
both machines for the solutions to be formulated in this study.
After testing the statistic equivalence of the two machines,
the stability in the process currently followed in D’vinia’s Buko
Pie is to be measured and validated. Both the data from oven A
(Machine 1) and oven B (Machine 2) were evaluated using
binomial capability analysis. Data points were subgrouped per
week, therefore each machine has three subgroups. It must be
noted however that it is generally recommended in binomial
capability analysis to use at least 25 subgroups, and so the
number of subgroups used in the study may be insufficient.
Setting the acceptable value at 11.65%, the corresponding
results for each machine are presented below.
Fig.7.P-chart of pies with burnt crust per week for oven A (machine 1).
Based from the p-chart provided by Minitab, it is shown that
the process in machine 1 is stable as there are no points that are
out of control. However, it can also be seen that the percentage
defective for machine 1 is 20.12%, as shown in the graph
below.
Fig.8. Cumulative percentage of pies with burnt crust per week produced in
oven A (machine 1).
This value exceeds the maximum acceptable percentage
defect of 11.65 %. Also, p-value was computed to be 0.84.
Since p>α, we can conclude that the percentage defective in
machine A is not acceptable.
After analyzing the process in machine 1, results for the data
obtained from machine 2 are as follows.
Fig.9.P-chart of pies with burnt crust per week for oven B (machine 2).
From the p-chart for the samples gathered from Machine 2,
it can be observed that an unusually low proportion of burnt
pies were gathered in week 1 while an unusually high
proportion of burnt pies were obtained from week 2. This may
suggest that the process used for Machine 2 is out of control.
To validate this, the percentage defective in the machine was
also calculated.
Fig.10. Cumulative percentage of pies with burnt crust per week produced in
oven B (machine 2).
Percentage defective for the data is 29.77%, which is higher
than the accepted value 11.65%. Furthermore, it was calculated
that p=0.53. Since p>α, it can then be concluded that for
Machine 2, the percentage of defective pies are higher than
11.65%.
B. Analysis
Attached is the Ishikawa diagram for the effect “D’Vinia’s
Buko Pie produces pies with burned crusts” (see Appendix E).
There are two categories considered in the diagram
construction, namely MATERIAL and METHOD. Branching
from the diagram are the first-level causes, further elaborated
in the why-why analysis for respective domains (see Appendix
F.1, F.2).
Controllable
For the method, the root causes identified as controllable
factors are the following: (i) there is no defined delegation of
work, (ii) they lack bakers, and (iii) the baking area is not
properly lit
The first two root causes are hypothesized to be attributed
to the number of available workers. Since the baker shoulders
other responsibilities aside from baking, the study included the
absence of delegation of work to be a root cause. However,
based from the interview, each worker has a specific task to do,
assigned to him/her by the management. Hence, it can be
controlled by adhering to the task delegation, effective during
working hours. Meanwhile, the second root cause presumes
that the bakers are seemingly low in number. However,
observation shows that the baker has extra times which he
devotes to other activities. Such activities include shouldering
other task, idling, etc. Therefore, this is not a true root cause.
For the third root cause, it observed that the light intensity
in the working area is insufficient with only one light bulb
present. This can be controlled by following the guidelines on
illimunation as provided by the Occupational Safety and Health
Association (OSHA). Baking which necessitates moderate
discrimination of detail would require a minimum light
intensity of 200 lux [27]. This can be achieved by increasing
the number of luminaires inside the area.
For the material, only one root cause is identified to be a
controllable factor, that is, the use of available amount of dough
needs to be maximized in par with the volume of demand. This
results to inconsistent thickness of pie crust where thin pies are
significantly produced. This can be controlled by adhering to
an existing standard measure from recipes made available for
commercial purposes.
Experimental
The root causes identified as experimental are the following:
(i) no one is assigned for maintenance, (ii) there is no defined
or specific method for maintenance of machine, and (iii) the
temperature reader has already exceeded its useful life.
Since the method of baking is very sensitive to temperature
[28], the crust would likely burn if baked in high temperature
relative to the allowed range. The baker has no mean of
adjusting the temperature with the reader broken. The study
attributes this to the maintenance of the oven, or the
component’s useful life.
The maintenance of the oven can either be lacking or not
well-defined, as the study implicated. Based from the
interview, it is determined that there exists a maintenance for
the oven thus the absence of maintenance due to unavailability
of personnel is not a true root cause. However, although the
management claims that the maintenance for the machine is
present, the machines still yield a significant number of defects
based from the data gathered. This is attributed to how effective
the maintenance schedule affects the performance of the oven.
The oven’s useful life is sixteen years [29] whereas the
ovens used in D’Vinia’s has been operational for more than
twenty-four years. This proves that the oven has indeed
exceeded its economic life which warrants either replacement
or overhaul.
Other experimental factors include (i) the spatula is made of
metal and (ii) the area where the pie is held is too small. During
data gathering, it is observed that the spatula used for placing
the pies inside the oven is operationally unstable. The lack of
stability is caused by the slippery surface of the metal and its
small surface area. The metal spatula, when contact with the
metal mold becomes more slippery. While placing the pies, it
is likely to slip off and touch the sides of the oven which is,
according to the baker, very hot.
Noise
Two non-controllable factors are identified which are as
follows: (i) there is a defined delegation of work but the
employees do not follow it, and (ii) company is not willing to
enlist assistance from external entities
Baking time is influenced by the amount of attention which
the baker devotes to. During data gathering, the worker is
unable to keep his full attention to baking as he shoulders other
responsibilities. This is attributed to the employee’s will to
disobey the prescribed task division. Meanwhile, the effectivity
of the maintenance schedule depends on the management’s
decision to enlist assistance external to the business.However,
this unwillingness is beyond the control of the study as this
relies on the managerial decision of the business owner.
V. RECOMMENDATIONS
Exceeding the useful life of the in-house thermometer is
among the identified root causes during the analysis of the
diagram. The study proposes the replacement of the oven by
purchasing at a cost of PhP45,000. This is assumed to cover the
installation of the equipment, as well. The oven would have the
following specification [30, 31]:
o Model No: XXX-XX
o Type: Electric bread oven
o (Capacity: 1 Tier /2 Tray)
o Size: 1330mm x 930mm x 630mm
o Power Supply: 220V/50Hz
o Power: 60W
o Color: Silver
o Materials: Stainless Steel
Furthermore, it is assumed that the oven would be able to
produce the desired performance level, as suggested by the goal
of the study. That is, the percentage defective from the new
oven would be nearly 11.65 per cent. Also, it would not
implicate maintenance unless it exceeds its useful life of sixteen
years.
Meanwhile, in response to the lack of effective maintenance
schedule, the study proposes to lay out a maintenance routine
as alternative to oven replacement. The maintenance would
cover the cleaning of the oven, thorough parts inspection and
provision of recommendations upon detection of mechanical
defect.
LBC Bakery Equipment suggested that during cleaning, it
is imperative to use proper cleaners and tools such as alkaline,
alkaline chlorinated or non-chloride containing cleaners with
soft cloths, soft bristled brushes, plastic scrapers and plastic
scouring pads. Adopting LBC’s manual for LRO equipment
weekly cleaning, the actions below should be followed:
Let unit cool
Sweep floor with heat resistant broom
Clean both sides of oven window with mild soap and
water
Clean control panel with mild soap and water
Clean handle with mild soap and water
Clean interior stainless steel surfaces with a stainless
safe cleaner such dish soap, ammonia, detergent and
medallion [32]
Apart from cleaning, maintenance would include the
checking of the oven door seal and calibration of the oven’s
temperature. If the door is not sealed properly, the heat can
escape from the oven, thus expending longer baking time and
increasing utility bills. Personal inspection is sufficient to
ensure properly sealed oven doors. As for the oven’s
temperature, additional equipment, such BakeWATCH®, can
be employed to monitor temperature for accuracy.
BakeWATCH® is a profiling kit designed to measure, record
and document temperature variations in both baked goods and
oven. Further details are provided in their website where the
user can request a quotation for purchasing the software [33].
Fig.11.BakeWATCH® [32]
The maintenance would cover three hours per day, a day per
week and each week per month. In conjunction with the
interview, the management specified that production is lightest
on Monday, thus it would be optimal to implement the schedule
during this day. The estimated maintenance cost, projected on
annual planning horizon, is equal to PhP8,388.
Shown below is the illustration of the cash flow between
two alternatives, helpful in assessing the economic impact of
both actions.
TABLE VI
CASH FLOW FOR SPECIFIED ALTERNATIVES
Retain old oven Replace oven
Capital investment 9,000 45,000
Expected annual
revenue 6,628,400 6,949,600
Maintenance cost 8,388 0
Salvage value at end
of useful life (N=16) 0 9,000
AW (15%) 6.62M 6.94M
Computing for the annual worth of both alternatives,
replacing the oven would yield a higher annuity compared to
that of retaining the old oven. The difference between the
equivalences amounts to PhP323,704.70.
In the evaluation of both alternatives, the study considers
three criteria, namely, revenue increase (RI), defect reduction
(DR) and implementation cost (IC). Attached is the detailed
breakdown of each criteria (see Appendix G).
The revenue increase is measured by ratio of the expected
annual revenue with the new alternative over status quo. The
defect reduction pertains to the percentage down shift of baked
pies with burnt crust. While, the implementation cost refers to
cost projected as annuities over the oven’s useful life with the
marginal attractive rate of return set at 15%.
TABLE VII
FACTOR RATING FOR SPECIFIED ALTERNATIVES
Alternative DR
(25%)
IC
(35%)
RI
(40%) Total
Maintenance
Schedule 1 2 1 1.35
New Oven 3 3 2 2.60
Table VII shows the factor rating for the alternatives
presented. Note that this considers one oven, however since it
is statistically proven that both exhibit the same performance,
the number of ovens would not significantly influence the
decision to which alternative would be implemented. Note that
the amount of revenue increase has the greatest weight, having
been implicated in the interview with the management.
For maintenance schedule, the study supposes that it would
not be able to reduce the percentage defect however would not
worsen it either, thus it remains the same. The implementation
cost is equal to PhP9,899.10. There is no expected revenue
increase with performance level remaining the same.
On the other hand, replacing the oven would mean a
reduction of baked pies with burnt pie crust by 49.96%. The
implementation cost is equal to PhP7,394.40. The expected
annual revenue is expected to be increase to PhP6,949,600
which is one and one-twentieth of the former revenue.
Summing the weighted ranks for both alternatives, it is
concluded that purchasing new ovens would be the preferred
alternative. It is expected to lower the percentage defective to
11.95% if the assumptions are met and that no external source
of variability factors in.
VI. SUMMARY AND CONCLUSION
D’Vinia’s Buko Pie and Food Products is a bakeshop
situated in Laguna which sells special buko pies, among other
baked goods, to their outlet stores. However, data for the last
three weeks show that significant percentage of the baked pies
have burnt pie crust which is attributed to the oven’s capability
and human factors.
In conjunction with the factor rating, it is recommended that
the management replace the ovens, with budget limited to
PhP45,000. The ovens would decrease the proportion of burnt
pies by 49.96% and level the performance between the ovens.
If the alternative follows through as expected, the mean annual
revenue would equal to PhP6,949,600. Moreover, improved
quality of buko pies can also be translated to soft savings with
increased customer patronization and sustained market
leverage.
VII. AREAS FOR FURTHER STUDY
Aside from investigating the recurrence of burnt pie crust in
the daily batch production of special buko pie in D’vinia’s
Buko Pie and Food Products, it is suggested that the study focus
on other defects or products within the bakeshop. Possible
nonconformities include unfinished or incomplete products,
non-uniform weights or sizes among same goods, or even signs
of contamination such as molds, detection of small insects,
rocks, hair in the product, etc. In line with this, the quality of
service within the stores can be evaluated as well in which most
of their business significantly depends on.
VIII. REFERENCES
[1] Retrieved October 2, 2014 from
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APPENDIX A
SUMMARY OF DATA COLLECTED FOR THREE (3) WEEKS
MACHINE 1
12-Oct-14
Sample Number Time Number of Inspected Pies Number of Pies with 'Defect'
1 4:00 8 0
2 4:15 8 1
3 4:23 6 1
4 4:27 4 0
5 4:29 3 0
6 4:30 1 0
7 4:35 3 1
8 4:40 1 0
9 4:45 4 0
10 4:48 4 0
11 4:50 4 3
12 4:56 4 0
13 5:00 4 1
14 5:03 7 1
15 5:05 1 0
16 5:10 6 4
17 5:12 1 1
18 5:20 4 3
18-Oct-14
Sample Number Time Number of Inspected Pies Number of Pies with 'Defect'
1 4:28 4 1
2 4:30 2 0
3 4:36 3 0
4 4:48 4 0
5 4:50 4 0
6 4:53 6 1
7 4:59 2 2
8 5:05 8 0
9 5:10 4 0
10 5:19 2 0
11 5:22 6 1
25-Oct-14
Sample Number Time Number of Inspected Pies Number of Pies with 'Defect'
1 4:13 7 0
2 4:15 8 0
3 4:38 2 0
4 4:40 6 0
5 4:48 8 2
6 5:00 8 0
7 5:02 3 3
8 5:04 5 5
9 5:19 3 2
10 5:23 1 1
APPENDIX A (cont’d)
SUMMARY OF DATA COLLECTED FOR THREE (3) WEEKS
MACHINE 2
12-Oct-14
Sample Number Time Number of Inspected Pies Number of Pies with 'Defect'
1 4:15 8 0
2 4:18 6 0
3 4:20 2 0
4 4:35 7 1
5 4:40 6 0
6 4:42 1 0
7 4:50 8 1
8 4:56 7 1
18-Oct-14
Sample Number Time Number of Inspected Pies Number of Pies with 'Defect'
1 n/a 7 3
2 4:43 8 4
3 4:58 12 11
4 5:01 2 2
27-Oct-14
Sample Number Time Number of Inspected Pies Number of Pies with 'Defect'
1 4:24 8 3
2 4:27 8 2
3 4:52 8 1
4 4:56 8 0
5 5:02 8 2
6 5:18 4 3
7 5:27 13 5
APPENDIX B
FLOW DIAGRAM
APPENDIX C
OPERATIONS PROCESS CHART
APPENDIX D
FLOW PROCESS CHART
APPENDIX E
ISHIKAWA DIAGRAM
APPENDIX F.1
WHY-WHY ANALYSIS (METHOD)
APPENDIX F.2
WHY-WHY ANALYSIS (MATERIAL)
APPENDIX G
CRITERIA FOR FACTOR RATING
Revenue increase
Let X be the ratio of the new annual revenue from the selected alternative to the current alternative
Criteria Rating
0 ≤ X < 1 1
1 ≤ X < 2 2
2 ≤ X < 3 3
3 ≤ X < 4 4
4 ≤ X < 5 5
Implementation cost
Criteria Rating
The annual implementation cost within 16 years ranges from 10,000-12,000 1
The annual implementation cost within 16 years ranges from 8,000-10,000 2
The annual implementation cost within 16 years ranges from 6,000-8,000 3
The annual implementation cost within 16 years ranges from 4,000-6,000 4
The annual implementation cost within 16 years ranges from 2,000-4,000 5
Defect reduction
Description Rating
The alternative has been able to reduce the percentage defective by 20% or below 1
The alternative has been able to reduce the percentage defective by 40% or below, but above 20% 2
The alternative has been able to reduce the percentage defective by 60% or below, but above 40% 3
The alternative has been able to reduce the percentage defective by 80% or below, but above 60% 4
The alternative has been able to reduce the percentage defective by 100% or below, but above 80% 5
APPENDIX H
PERTINENT COMPUTATIONS
Average daily production
𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑖𝑛𝑠𝑝𝑒𝑐𝑡𝑒𝑑 𝑝𝑖𝑒𝑠
𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑑𝑎𝑦𝑠=
300
3= 100
Expected proportion defective
𝑤𝑀𝑎𝑐ℎ𝑖𝑛𝑒 1 ∗ %𝑑𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒𝑀𝑎𝑐ℎ𝑖𝑛𝑒 1 + 𝑤𝑀𝑎𝑐ℎ𝑖𝑛𝑒 2 ∗ %𝑑𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒𝑀𝑎𝑐ℎ𝑖𝑛𝑒 2 =
39(34169⁄ ) + 19(39
131⁄ )
39 + 19= 0.2328
Expected annual revenue (in PhP)
𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑑𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒 ∗ 𝑃𝑟𝑖𝑐𝑒 ∗ 365 𝑑𝑎𝑦𝑠 + 𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑛𝑜𝑛 − 𝑑𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒 ∗ 𝑃𝑟𝑖𝑐𝑒 ∗ 365 𝑑𝑎𝑦𝑠 =
23(120)(365) + 77(200)(365) = 6,628,400
Expected annual losses (in PhP)
𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑑𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒 ∗ 𝐿𝑜𝑠𝑠 ∗ 365 𝑑𝑎𝑦𝑠 =
23(80)(365) = 671,600
Percentage of losses from annual revenue
𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑙𝑜𝑠𝑠𝑒𝑠
𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑎𝑛𝑛𝑢𝑎𝑙 𝑟𝑒𝑣𝑒𝑛𝑢𝑒=
671,600
6,628,400= 0.1013
Percentage shift in defective items
𝐺𝑜𝑎𝑙 𝑣𝑎𝑙𝑢𝑒
𝐶𝑢𝑟𝑟𝑒𝑛𝑡 %𝑑𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒=
0.2328 − 0.1165
0.2328= 0.4996
Maintenance cost (in PhP)
𝑀𝑖𝑛𝑖𝑚𝑢𝑚 𝑤𝑎𝑔𝑒
8 𝑙𝑎𝑏𝑜𝑟 ℎ𝑜𝑢𝑟𝑠(
3 𝑙𝑎𝑏𝑜𝑟 ℎ𝑜𝑢𝑟𝑠
𝑑𝑎𝑦 ) (
1 𝑑𝑎𝑦
𝑤𝑒𝑒𝑘) (
4 𝑤𝑒𝑒𝑘𝑠
𝑚𝑜𝑛𝑡ℎ) (
12 𝑚𝑜𝑛𝑡ℎ𝑠
𝑦𝑒𝑎𝑟) =
466
8(3)(1)(4)(12) = 8,388
Expected annual revenue1 (in PhP)
𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑑𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒 ∗ 𝑃𝑟𝑖𝑐𝑒 ∗ 365 𝑑𝑎𝑦𝑠 + 𝐸𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑛𝑜𝑛 − 𝑑𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒 ∗ 𝑃𝑟𝑖𝑐𝑒 ∗ 365 𝑑𝑎𝑦𝑠 =
12(120)(365) + 88(200)(365) = 6,949,600
Goal
0.2328 − 0.7(0.2328 − 0.0667) = 0.1165 (~11.65%)
1 With new oven
Annual Worth (Retain old machine)
−9,000 (𝐴
𝑃, 15%, 16) + 6,628,400 − 8,388 = 6,618,500.90
Annual Worth (Replace machine)
−45,000 (𝐴
𝑃, 15%, 16) + 6,949,600 + 9,000 (
𝐴
𝐹, 15%, 16) = 6,942,205.60
Implementation Cost (Retain old machine)
8,388 + 9,000 (𝐴
𝑃, 15%, 16) = 9,899.10
Implementation Cost (Replace machine)
45,000 (𝐴
𝑃, 15%, 16) − 9,000 (
𝐴
𝐹, 15%, 16) = 7,394.40