POINT ALLOCATION BASED QUALITY CONTROL AND DEFECT ANALYSIS IN SEWING SECTION OF A WOVEN FACTORY OF...

Published in Dhaka University Journal of Management; Vol 5, Nos 1 & 2; Jan-Dec-2013

POINT ALLOCATION BASED QUALITY CONTROL AND DEFECT

ANALYSIS IN SEWING SECTION OF A WOVEN FACTORY OF

BANGLADESH FOR SHIRT MANUFACTURING

Md. Noman Hossain Chowdhury 1, Shabab Al Haque

2

1Assistant Professor, State University of Bangladesh (SUB),

[email protected]

2 Industrial Analyst, [email protected]

Abstract

Since inception from 1970, Bangladesh’s garments export industry showed consistent growth and has become one of

the driving forces of the country’s economy. To sustain this position in global competitive environment, improving

and maintaining of quality is indispensible. Defects in products challenge the value creation process of any assembly

line of a factory. Garment manufacturing is no exception. Having an efficient quality control practice ensures fewer

defective garments products and reduced wastage of resources expensed for re-works. This paper suggests point

allocation based quality control method over other methods and presents a comprehensive study on types and

frequencies of defects that occur in shirt manufacturing process the objective of which is to provide management with

an insight regarding the nature of defects mostly experienced by workers. This would eventually help management in

planning for defect-detection training and would provide clearer picture regarding scope and priorities of quality

control training programs.

Key Words: Garments, Defects’ Analysis, Point Allocation System, Quality control, Woven, Shirt manufacturing

1 INTRODUCTION

Thanks to many macroeconomic factors, Bangladesh has placed itself as one of the leaders in

garments domain in the world. Since the inception of its garments export industry in the late

1970s, its RMG export levels grew steadily and has become a top with around USD 15 billion

in export value in calendar year 2010. With 12 percent annual growth rate clothing exports are

the key driving force behind GDP development (7% CAGR from 1995-2010) [1]

.

In order to sustain this position in global competitive environment, improving and

maintaining of quality is indispensible. Improved quality accounts for customer satisfaction

and consistent customer demand.

Every assembly operation in an apparel floor adds value. Defects in products challenge this

value creation process. Having an efficient quality control practice in place and efficient

detection of defects in products ensures fewer defective garments products and reduced

wastage of resources expensed for re-works.

This paper presents study on a renowned garments factory’s sewing section. This study tries

to conduct a comparative analysis over different quality control approaches with respect to

level of motivation they create among workers, resource cost involved with each of the

approaches. The study also conducted a comprehensive study on types and frequencies of

defects that occurs in shirt manufacturing process in order to provide management with an

insight regarding the nature of defects mostly experienced by workers. This would eventually

help management in planning for defect-detection training and would provide clearer picture

regarding scope and priorities of quality control training programs.

1.1 Problem Definition and Methodology

As stated in the preceding chapter, the objectives of this study are as follows:

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mailto:[email protected]


1. Suggesting Point Allocation System (PAS) in place of existing quality control

approaches.

2. Analysis to find out the most defect-prone operations in a typical shirt Manufacturing

assembly line.

3. Pareto analysis of different types of defects in order to find out the most frequent

defects in each of the most defect-prone operations.

Defect-data for 6 months of a year related to shirt manufacturing was collected from the

apparel manufacturing plant.

2 LITERATURE REVIEW

2.1 Quality Control

In every industry, quality of product is of great importance. Garments industry is of no

exception. To be precise, in present days of cut-throat competition and globalization, quality

control for garments industry has got immense attention. Economy of Bangladesh largely

depends on the garments industry. So, producing of quality products should be our topmost

concern in order to remain in the competition. Quality retains the customers and increases

profit margin as well. Customers all over the world have become so demanding for good

quality goods that, quality is no longer a competitive advantage, but it is becoming a sheer

necessity to survive in the marketplace. Therefore, quality has to be designed and built into

products[2]

and not just “inspected” into products.

2.2 What is quality?

It is the goodness or badness in a product. This definition holds true till this date. However,

in general terms, quality encompasses important characteristics of a product for which, it

is in demand[3]

. Quality is also referred to as “conformance to requirements"[4]

. ISO 9000:

2000 defines quality as “degree to which a set of inherent characteristics fulfill

requirements”[5]

.

Some of the other ways of definition of quality includes but not limited to:

1. "A combination of quantitative and qualitative perspectives for which each person has

his or her own definition; examples of which include, "Meeting the requirements and

expectations in service or product that were committed to" and "Pursuit of optimal

solutions contributing to confirmed successes, fulfilling accountabilities". In technical

usage, quality can have two meanings:

a. The characteristics of a product or service that bear on its ability to satisfy stated or

implied needs;

b. A product or service free of deficiencies."[6]

2. "Quality combines people power and process power."[7]

3. Deming concentrating on "the efficient production of the quality that the market

expects,"[8]

and he linked quality and management: "Costs go down and productivity

goes up as improvement of quality is accomplished by better management of design,

engineering, testing and by improvement of processes."[9]

4. "Quality in a product or service is not what the supplier puts in. It is what the

customer gets out and is willing to pay for."[10]

5. According to Juran: "Fitness for use."[11]

Fitness is defined by the customer.

6. "Uniformity around a target value."[12]

It is hard to quantify quality in absolute terms, rather can only be judged in terms of standards

or quality benchmarks.


There are numerous factors that need to be considered while defining quality of a product.

Appearance, design, measurements, safety, relevance, price etc. are some quality factors.

There are some other factors which are related to processes as well. Man, Machine, Material,

Method and Money (i.e 5M) addresses quality of processes.

2.3 Inspection

Inspection routines must be operated to check whether an item or operation meets the specific

range of acceptable quality. The ultimate goal of inspection is to find out the faults in the

earliest phases possible.

In garments industry, inspection is mainly performed in three stages:

(i) Inspection of raw materials

(ii) In-line inspection

(iii) End-line inspection

On reception of raw materials like fabric, zipper, labels, thread etc. from vendors, this first

phase of inspection is conducted. In-line inspection is in-process inspection and done while

the process is on or during intervals of consecutive processes. Traffic Light System, an in-line

inspection process is becoming popular over the last few years. End line inspection is

conducted at the end of processes focusing on overall inspection for all types of faults. In the

following chapters some of the inspection methods are discussed.

2.4 Four-Point System

Four-point system is related to Fabric inspection. As soon as the vendor supplies fabric, the

role of fabric is unwinded and passed over a special inspection table and then two inspectors

inspect the fabric.

2.5 Traffic Light System (TLS)

Traffic Light System (TLS), a statistical approach, is widely used in in-line inspection. If

appropriately implemented, TLS creates motivation or quality awareness among the workers.

In this system, each operator is given a job card with quality points. A TLS job card is shown

in Table 2-1.

Table 2-1: TLS Job Card

In this factory where the study was conducted, a Quality Control Inspector (QCI)

takes 7 pieces of sample from a bundle and checks those pieces. If there found a

single defect, the operator is penalized with a red or yellow mark on the TLS Card.

This way, each operator is checked 4 times a day - 2 times at AM and 2 times at PM.

For an error-prone worker, the frequency may be higher (that's why there are 4 boxes

instead of 2 for each of AM and PM in the TLS Card).

Evaluation of a worker in the TLS is done in the following ways:

If the current grade is Green, next fault would cause it to be Yellow, otherwise

the code would remain Green.


If the current grade is Yellow, next fault would cause it to be Red, otherwise

the code would remain Yellow.

If the current grade is Red, next ‘no-fault’ would make it Yellow and next 3

‘no-fault’ would yield it to Green. Any single fault in the next 3 samples

would yield it to Red again.

After one month, the performance would easily be evaluated. More red marks

definitely mean bad performance.

TLS has some demerits. It has tendency to evaluate tough-job-operators poorly while

awarding easy-job operators. Uniform sampling from all the operations should yield

better results.

2.6 Acceptance Sampling

Before the shipment of finished garments, it is necessary (for the buyer/consumer) to

inspect the lot. The objective of this inspection is to find out whether to accept the lot

or reject it. Accepting a lot without inspection is unusual in garments industry. On the

other hand, sometimes it involves 100% inspection where every single item is

inspected. Though 100% inspection naturally means high quality, at the same time, it

involves cost and time.

Acceptance sampling method is a very popular and widely accepted method in

inspection. This method decides sample sizes and criteria for accepting or rejecting

the lot in statistical method. In acceptance sampling, a sample is taken from the lot,

and some quality characteristics of the units in the sample are inspected. Then, a

decision is made regarding lot disposition. Usually the decision is either to accept or

to reject the lot.

Some aspects of acceptance sampling are needed to be kept in mind. Its purpose is to

'sentence' lots, not to estimate the lot quality. Most acceptance sampling plans are not

designed for estimation purpose. Again acceptance sampling plans do not provide any

direct form of quality control. Acceptance sampling simply accepts or rejects lots.

Even if all lots are of same quality, sampling may accept some lots and reject others.

This is unlike process controls which are used to control and systematically improve

quality.

In comparison to 100% inspection, acceptance sampling has some advantages. It is

usually less expensive and involves less handling of the products. Fewer personnel are

involved in inspection activities. It often reduces the amount of errors in inspection.

Sometimes the rejection of entire lots as opposed to the simple return of defectives

often provides a stronger motivation to the vendor for quality improvements.

There are some disadvantages of acceptance sampling, as well. There are risks of

accepting ‘bad’ lots and rejecting "good" lots. Less information is usually generated

about the product or about the process that manufactured the product. Acceptance

sampling requires planning and documentation of the acceptance sampling procedures

whereas 100% inspection does not require this.

2.7 Types of Sampling Plans

There are number of different ways to classify acceptance sampling plans. One major

classification is by attributes and variables. Variables, of course, are quality

characteristics that are measured on a numerical scale. Attributes are quality

characteristics that are expressed on a "go, no-go" basis.


Sampling plans can also be classified on how many samples are to be taken from the

lot. Thus, sampling plans can be classified as - single sampling plan, double sampling

plan and multi-sampling plan. Multi-sampling plan is not used commonly in the

garments industry.

A single sampling plan is a lot-sentencing procedure in which one sample of n units

is selected at random from the lot, and the disposition of the lot is determined based

on that sample. For example, a single-sampling plan for attributes would consist of a

sample sized n and an acceptance number c. If there are c or fewer defectives in the

sample, accept the lot, and if defective items in that sample are more than c, then

reject the lot.

Double-sampling plans are somewhat more complicated. Following an initial

sample, a decision based on the information in that sample is made either to accept or

reject the lot or take a second sample. If the second sample is taken, the information

from both the first and the second sample is combined in order to reach a decision

whether to accept or reject the lot.

A multiple-sampling plan is an extension of the double-sampling concept, where

more than two samples may be required in order to reach a decision regarding the

disposition of the lot. Sample sizes in multiple sampling ate usually smaller than they

are in either single or double sampling.

The ultimate extension of multiple sampling is sequential sampling, in which units are

selected from the lot one at a time, and following inspection of each unit, a decision is

made either to accept the lot, reject the lot, or select another unit.

3 PROJECT WORK

On completion of the study on all the process and quality control system in the sewing

section of a shirt manufacturing floor, we have proposed Point Allocation System

(PAS) based quality control. The Sewing Section addressed in this study uses Traffic

Light System (TLS). For an effective PAS in practice, workers need to be trained in

defects’ checking. As the number and types of defects found in a sewing section is

quite large, management can opt for staring with the most frequent defects. For this a

comprehensive study has been conducted on 6 months’ data on defect types. After

analysis, this paper lists the operations in a sewing section that are the most defect

prone as far as Average Defect Rates (ADR) are concerned. Then this paper puts light

on those most defect-prone operations in order to list the defect types that are most

frequent.

3.1 Point Allocation System (PAS)

In the proposed method, Point Allocation System (PAS), workers themselves will be

considered as quality controllers. They will evaluate their own work and will make

sure that they produce defect-free products. Eventually, they would act more carefully

and would be trained for having clearer picture regarding specifications and necessary

treatments for each fault.

The required training and awareness will be provided to the workers. Special care

would be taken for tougher job operators so that their defect-rate reaches close to that

of easy-job workers. They should attain the capability of understanding requirements

merely by observing the sample and specifications hanged in the line.

For this, Quality Circles may be introduced. Each Quality Circle will include

operators of similar type of jobs led by the most skilled and experienced operator or


even by a production supervisor. Members of the Quality Circles will sit once in a

week to discuss their jobs, problems faced as well as share the solutions with

management. Every meeting should have tangible outcome with problems defined

and solutions proposed. Provision might be introduced for rewarding the best

effective or creative solution.

Thus required number of Quality Control Inspectors (QCI) and Supervisors would

become less. The floor supervisor will act like a floating Quality Controller and look

after all the line activities and the operators will consult with him as soon as they find

any problem. Each of the workers will be provided with a PAS Card (Figure 3-1).

Also, the Quality Supervisor will bear some tokens.

Figure 3-1: PAS Card

The Application of the PAS Card will be as follows:

A worker/operator will notify Quality Supervisor as soon as he/she finds a

fault in items in hand passed to him/her from another operator. The Supervisor

will give him one token.

Then, Supervisor will find out the operator/worker who is accountable for the

fault. On the PAS Card of that operator/worker, under the column 'Number of

Faults Committed', the Supervisor will mark a circle.

At the final hour of the day-work, the Supervisor will visit those who have

received token(s). Now, under the column 'Faults Found', he will mention the

number of token(s) received by the operator and give an initial.

After one month, total 'Number of Faults Committed' and total 'Faults Found'

will be calculated. Now total 'Faults Found' will be subtracted from total

'Number of Faults Committed' and the result will be considered as the 'Net

Faults'.

The operator with the least 'Net Faults' will be awarded with incentives.

3.2 Advantages of PAS

As in this system, the workers are allowed to compensate their 'Number of

Faults Committed' by finding faults committed by others. So, the workers

would be motivated to give more concentration so that others get less number

of faults in there works. Also, as they will try to compensate their number of


faults by finding faults committed by others, there will be less chance for a

defective item to pass out.

Every worker now plays a role of quality checker, which will be a motivating

factor for the workers.

There will be significant cost savings due to decrease of number of Quality

Inspectors.

3.3 Finding Critical Operations

Sewing Section is divided into two main sections according to functionalities: Make

Section and Body Section. Make Section is responsible for producing collar and cuff

while the Body Section assembles the collar and cuff with the main body and sleeve

of the shirts. Different parts of a shirt are demonstrated in Figure 3-2.

Figure 3-2: Different parts of Shirt

Operations involved in Make Section for an ideal Collar and Cuff as well as Body

section of a shirt are provided as flowcharts in Figure 3-3, 3-4 and 3-5.


Pocket Rolling

Pocket Pressing

Front Placket (at

upper front)

Pocket Attach (at

upper front)

Back Tuck + Care

Label Attach

Main Label Attach

(at Yoke)

Back Yoke Joint

Back Top Stitch

Lower Front

Rolling

Front/Shoulder

Joint Placket Attach

Sleeve

Sleeve Joint

Arm Hole Top

Stitch

Side Seam

Collar Mark

Cuff Mark +

Sleeve Mark

Collar Joint

Cuff Attach

Collar Top Stitch

Bottom Hem

Hole Stitch

Button Attach

Thread Cutting

Gambol Cut

Gambol Tuck

Gambol Joint

Figure 3-3: Process Flowchart of a Make section


Lining

Ironing

Fusing

Collar sewing

Collar turning

Forming

Collar top Stitch

Collar Bottom

Cutting

Band interlining

Band fusing

Band rolling

Collar band join

Collar band top

stitch

Collar band bottom

Cutting

Figure 3-4: Process flowchart for making Collar

Cuff lining

Cuff fusing

Cuff Rolling

Cuff sewing(&

Inlay cutting

Cuff top Stitch

Hole Stitch

Button Attach

Figure 3-5: Process flowchart for making Cuff

At the end of every month, the TLS Card for every operator is evaluated and the

Average Defective Percentage (ADP) is calculated. ADP is calculated with the

following formula:

ADP = ( # of defectives found / Total # of units inspected) X 100 %


ADPs are used to find out critical operations with high defect rates. Operations having

Average ADPs below 3% are usually considered as satisfactory. Our study shows

that, the critical operations having Average ADPs above 3% are as follows:

Collar Band Joint - 3.44%

Front Placket-3.83%

Main Label -3.37%

Pocket Attach - 5.53%

Placket Attach Sleeve – 5.79%

Sleeve Joint - 6.12%

Arm-hole Top Stitch -7.16%

Side-Seam - 7.96%

Collar Joint – 7.17%

Cuff Attach - 8.43%

Collar Joint Top Stitch - 5.99%

Bottom Hem - 7.07%

3.4 Study and analysis of Most Frequent Defects

Now, the critical and fault-prone operations are sorted out, the training program

should be designed giving importance on them.

For every critical and error-prone operation listed above, six months’ comprehensive

data on reports of different types of defects were collected in following paragraphs.

From those tables, one can easily get idea regarding types of defects that are most

common for each of the operations [Table 3-1].

Table 3-1: Common Defect Types

# Operation Defect type

1 Collar Band

Joint

Nose Up Down

Width Irregular

2 Front Placket Skip Stich

3 Main Label

Attachment

Label Bias

Raw Edge

4 Pocket Attach

Bad Shape

Check Bias

Width Irregular

Slip Stich

T Tension

5 Placket Attach

Sleeve

Uneven Point

Width Irregular

Bad Shape

Improper Stich


Slip of Stich

6 Sleeve Joint

Check Bias

Skip Stich

C/L Reverse

Open stich

Puckering

C/L Displaced

7 Arm Hole Top

Stich

Raw Edge

Width Irregular

Top side loose

8 Side Seam

Raw Edge

Pleat

Skip Stich

Intersection Point

U/D

Width Irregular

9 Collar Joint Allowance Uneven

Puckering

1

0 Cuff Attachment

2-PKT Up-down

Width Irregular

Check Bias

Improper back

Stich

Pleat

Projection

Slip of Stich

1

1

Collar Joint Top

Stich

Allowance uneven

Puckering

1

2 Bottom Hem

2-Front Check

Uneven

Bad Shape

Width Irregular

Skip Stich

Projection

Without Back

Stich

Based on the tables, pareto charts are produced in order to see the most frequent

defects in each of the processes.


Figure 3-6: Pareto chart with common Defects in for Collar Band Joint

From Pareto chart of defects, we can see that Nose Up-Down is the most frequent

defect in Collar Band Joint, the reason of which includes lack of adequate skill in

operators, defects in the shape of pattern and also defects in stiches made by top-stitch

operators.

Figure 3-7: Pareto Chart with common Defects in Front Placket

Skip-stitch is the most frequent defect in Front (Button and Box) Placket operation

which is caused mainly due to problems in machines, inaccurate positioning of

Needle-Point and mal-adjustment with Fabric and Machine. The second most frequent

defect (i.e. Number Mistake) is caused mainly due to lack of care by the operators.

Figure 3-8: Pareto Chart with common defects in Main Label attachment

Label Bias is the most frequent defect in Main Label Attachment operation which

might be caused mainly due to lack of attention while handling label and fabric,


inaccurate placing of label by Collar Top-Stich Operator, and defects in printing of

labels.

Figure 3-9: Pareto Chart with Common Defects in Pocket Attach

Bad shaping of pockets is found to be the most observed defect in Pocket Attaching

Operation that is in most cases caused by lack of proper ironing of pockets, unskilled

handling by attaching operators (lack of adjustment of stitching with marks),

inaccurate shape of ironing pattern, defects in marking by marking operators etc.

Figure 3-10: Pareto Chart with common defects in Placket Attach Sleeve

Defects of Uneven Point in Sleeve Placket are caused mainly by inadequate ironing,

mal-handling by the operators, lack of care by Placket Attach Operator.


Figure 3-11: Pareto Chart with common defects in Sleeve Joint

Check bias defect is mostly observed in Sleeve Joint operation. This defect is mostly

observed in check fabrics. The defect is mostly caused due to lack of care in following

cut-mark while joining sleeves, un-skilled operators, uneven tension while feeding

fabric on both side of the joint (i.e. main part and sleeves).

Figure 3-12: Pareto Chart with common defects in Arm-Hole Top Stich

Defects of raw-edge in arm-hole top stitch are mainly caused by unskilled operators,

mal-adjustment between folder & fabric and defects in sleeve joints.


Figure 3-13: Pareto Chart with Common defects in Side Seam

Raw-edge defects in Side-Seam Joint Top Stitch is mainly caused by lack of skill in

operators, mal-adjustment of stitching-guide, and defects in machines etc.

Figure 3-14: Pareto Chart with common defects in Collar Joint

Defect of Uneven allowance in Collar Joint is caused mainly due to unskilled

operators, defects in Collar Neck Shape, problems in stitching guides.


Figure 3-15: Pareto Chart with common defects in Cuff Attachment

Two Plackets’ (inside and topside) up-down is mainly caused by defects in Cuff

Attachment marking, un-even cutting in sleeve mouth and lack of skill in operators.

Figure 3-16: Pareto Chart with common defects in Collar Joint Top Stitch

Uneven allowance in Collar Joint Top Stich is mainly caused by inadequate lack of

skill and concentration by the operators and defects in Collar Joints.


Figure 3-17: Pareto Chart with common defects in Bottom Hem

Two Uneven Front-Check defect in Bottom Hem stitching (mainly observed in check

fabrics) is mainly caused due to defects in Fabric Cutting Pattern, Shoulder Joint &

Collar Attachments.

3.5 Recommendations and Conclusion

As mentioned above, as the workers would play additional role as quality checkers,

very few number of fulltime Quality Inspectors should be enough for supervision.

But, at the same time, workers need to be trained in quality checking. A portion of the

cost savings from maintaining less number of Quality Inspectors might be invested for

training of the workers. Tougher-job operators should get proportionately more

intensive training than to easy-task operators.

One may argue that the productivity will decrease to a large extent when the workers

are loaded with additional task of checking items in hand for defects. But, one point to

note that, the main cost incurred by a defective item is in required reworks. Rework is

always more time consuming than completing an assembly straight. So, even the

productivity of workers would decrease to some extent, the cost saving from reworks

would be higher.

Surely for getting the workers ready for successful implementation of PAS, effective

training is indispensable. For this, training program focusing on the most frequent

defects would make things easier. In the following chapters our study provides a list

of the most frequent defects in each operation of sewing section of a shirt

manufacturing assembly line. Though this study was only focused to sewing section,

same kind of study can be done in future for other sections of assembly line for other

products as well.

Now, the critical and fault-prone operations are sorted out, the training program

should be designed giving importance on them. From section 3.5 (Analysis of

Defects), this is evident that, lack of skill in operators in many operations (i.e. Collar

Band Joint, Side-Seam Joint Top Stitch, Collar Joint, Two Plackets’ up-down, Collar

Joint Top Stitch) are the main cause of the most frequent defects. In addition, for


some operations (i.e. Front Placket, Main Label Attachment, Sleeve Placket, Sleeve

Joint operation), awareness needs to be build up among operators to be careful while

handling fabrics. Also training needs to be focused on some special skills like pattern

making, applying even tension while feeding fabric for stitching, accurate

adjustment of stitching guide etc.

4 REFERENCES

[1] Berg, Achim; Hedrich, Saskia; Kemph, Sebastian; Tochtermann, Thomas, “Bangladesh’s

Readymade Garments Landscape: The challenge of Growth” – Apparel, Fashion and Luxury

Practice-A research from McKinsey&Company, November 2011

[2] Mihta, Pradip V.; Bsardwaj, Satish K.. - “Managing Quality in the apparel Industry”- 1st

edition, Publication 1998

[3] Sultana, Afroza, “Study on Quality Control in Knit Garments Production”, Daffodil

International University, 2012

[4] Crosby, Philip (1979). Quality is Free. New York: McGraw-Hill. ISBN 0-07-014512-1.

[5] TC 176/SC (2005). ISO 9000:2005, Quality management systems -- Fundamentals and

vocabulary. International Organization for Standardization.

[6] American Society for Quality, Glossary - Entry: Quality, retrieved 2008-07-20

[7] Chowdhury, Subir (2005). The Ice Cream Maker: An Inspiring Tale About Making

Quality The Key Ingredient in Everything You Do. New York: Doubleday, Random House.

ISBN 978-0-385-51478-1.

[8] Edwards Deming, W. (1986). Out of the Crisis. Cambridge, Mass.: Massachusetts

Institute of Technology, Center for Advanced Engineering Study. ISBN 0-911379-01-0.

[9] Walton, Mary; W. Edwards Deming (1988). The Deming management method. Perigee.

p.88. ISBN 0-399-55000-3.

[10] Drucker, Peter (1985). Innovation and entrepreneurship. Harper & Row. ISBN 978-0-

06-091360-1.

[11] American Society for Quality, Glossary - Entry: Quality, retrieved 2008-07-20

[12] Taguchi, G. (1992). Taguchi on Robust Technology Development. ASME Press.

ISBN 978-99929-1-026-9.

http://en.wikipedia.org/wiki/International_Standard_Book_Number

http://en.wikipedia.org/wiki/Special:BookSources/0-07-014512-1

http://www.asq.org/glossary/q.html


http://en.wikipedia.org/wiki/Special:BookSources/978-0-385-51478-1








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