Quality Improvement in D'Vinia's Buko Pie through Reduction of Burnt Pie Crusts

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]

[email protected]

[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]

http://www.businessdictionary.com/definition/money.html

http://www.businessdictionary.com/definition/business-venture.html

http://www.businessdictionary.com/definition/expectation.html

http://www.businessdictionary.com/definition/income.html

http://www.businessdictionary.com/definition/assumption.html

http://www.businessdictionary.com/definition/characteristic.html

http://www.businessdictionary.com/definition/population.html

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.

http://www.businessdictionary.com/definition/inspection.html

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

http://www.sme.com.ph/membersuppliers/foodagriculture/supplier

s.php?page=dvinias_buko_pie. [2] Retrieved December 8, 2014 from

http://www.processma.com/documentation/CapabilityBinomial.ht

ml.

[3] Retrieved December 8, 2014 from

http://www.businessdictionary.com/definition/capital-

investment.html#ixzz3LKyDbuBg. [4] Retrieved December 8, 2014 from

http://www.investopedia.com/terms/c/cashflow.asp.

[5] Retrieved December 8, 2014 from http://www.informit.com/articles/article.aspx?p=412351&seqNum

=6.

[6] Retrieved December 8, 2014 from http://www.statcan.gc.ca/edu/power-pouvoir/ch10/5214864-

eng.htm.

[7] Retrieved December 8, 2014 from http://ids355.wikispaces.com/Ch.+8+Location+Planning+and+Ana

lysis.

[8] Retrieved December 8, 2014 from http://www.slideshare.net/kapiljain752/flow-process-chart.


http://www.mindtools.com/pages/article/newPPM_03.htm. [10] Retrieved December 8, 2014 from

http://www.businessdictionary.com/definition/hypothesis.html#ixz

z3LKtjBLKT. [11] Retrieved December 8, 2014 from

http://stats.oecd.org/glossary/detail.asp?ID=3675.

[12] Retrieved December 8, 2014 from http://www.princeton.edu/~achaney/tmve/wiki100k/docs/Ishikawa

_diagram.html.

[13] Retrieved December 8, 2014 from http://www.aub.edu.lb/hr/compensation/Documents/job_analysis_

description.pdf.

[14] Retrieved December 8, 2014 from http://engineeringandeconomicanalysis.blogspot.com/2013/12/min

imum-attractive-rate-of-return.html. [15] Retrieved December 8, 2014 from

http://www.informit.com/articles/article.aspx?p=412351&seqNum

=6. [16] Retrieved December 8, 2014 from

http://encyclopedia2.thefreedictionary.com/operation+process+cha

rt. [17] Retrieved December 8, 2014 from

http://decmod.diegoazeta.org/emv---eol.php.

[18] Retrieved December 8, 2014 from http://www.businessdictionary.com/definition/opportunity-

cost.html#ixzz3LK7mXaXD.

[19] Retrieved December 8, 2014 from http://www.pqsystems.com/qualityadvisor/DataAnalysisTools/p_c

hart.php.


http://www.financeformulas.net/Present_Value.html. [21] Retrieved December 8, 2014 from

http://www.henrygeorge.org/def2.htm.

[22] Retrieved December 8, 2014 from http://www.itl.nist.gov/div898/handbook/pmc/section3/pmc332.ht

m.

[23] Retrieved December 8, 2014 from http://www.investopedia.com/terms/r/revenue.asp.


http://www.businessdictionary.com/definition/rework.html#ixzz3LKAbv3rN.


http://www.referenceforbusiness.com/encyclopedia/Res-Sec/Salvage-Value.html#ixzz3LL13oUWf.

[26] M.A. Ramirez. (July, 2013). Manufacturing engineering. [Lecture

handout]. [27] Occupational Safety and Health Center. (May, 2013). Occupational

safety and health standards. [PDF].

[28] Haedrich, K., Pie: 300 Tried-and-True Recipes for Delicious Homemade Pie, The Harvard Common Press, 2004. Retrieved

December 9, 2014 from

http://books.google.com.ph/books?id=20FzM91fMI0C&pg=PA397&lpg=PA397&dq=baking+pie+sensitivity+to+temperature&sour

ce=bl&ots=fXdnM4Wk3B&sig=OrDYCWHzDefEJ9jtxyE8ak5M

PXU&hl=fil&sa=X&ei=UJqGVN6rGcv98QWxjIF4&ved=0CCkQ6AEwAQ#v=onepage&q=baking%20pie%20sensitivity%20to%

20temperature&f=false.

[29] (2) Retrieved November 20, 2014 from http://www.demesne.info/Home-Maintenance/Appliance-Life-

Expectancy.htm.

[30] Retrieved December 8, 2014 from http://www.olx.ph/index.php/view+classifieds/id/62711482/Bakin

g+Oven+Lpg-Bakery+Equipment-

For+Sale?referralKeywords=bakery+oven&event=Search+Ranking,Position,1-16,16.


http://cnverly.en.alibaba.com/product/1708647909-220137495/Gas_Type_Bakery_Oven.html.


http://www.langbakery.com/manuals.cfm. [33] Retrieved December 7, 2014 from http://www.bakewatch.com/

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


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


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


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


1 n/a 7 3

2 4:43 8 4

3 4:58 12 11

4 5:01 2 2

27-Oct-14


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





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




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