implementation of six sigma

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APPLICATION OF SIX SIGMA AT DAWLANCE

Group No. 30 Batch: 2010-2011

Name Seat No.

TARTEEL AHMED IM-041

USMAN GHANI IM-055

Internal Advisor: Mr. Ali Zulqarnain (Asstt. Professor)

Ms. Rabia Siddiqui (Asstt. Professor)

External Advisor: Mr. Tahir Bukhari

(Manager Quality Control)

DEPARTMENT OF INDUSTRIAL & MANUFACTURING

ENGINEERING, NED UNIVERSITY OF ENGINEERING & TECHNOLOGY

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CERTIFICATE

Submitted in partial fulfillment of the requirement of degree of Bachelor of

Industrial & Manufacturing Engineering.


Group No. 30 Batch: 2010-2011

Name Seat No.

TARTEEL AHMED IM-041

USMAN GHANI IM-055

RAFFAY BIN RAUF IM-070

SHAHBAZ BAIG IM-071

__________________ __________________

Internal Advisor(s) External Advisor

_____________ _____________

Examiner -1 Examiner -2

DEPARTMENT OF INDUSTRIAL & MANUFACTURING

ENGINEERING NED UNIVERSITY OF ENGINEERING & TECHNOLOGY

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ABSTRACT

Dawlance is the 7th most Favorite brand in Pakistan, out of 3500 brands. Research revealed

that Dawlance is in every second house hold in Pakistan, out of those households which have

appliances. Dawlance is considered to be the most ‘Reliable’ & ‘Innovative’ brand among all

home appliance brands in Pakistan.

The issue which has been highlighted in this project is the silicon filler, which is an expensive

imported item, and is being used to fill the gaps which are occurring due to bending of Front

Cross Piece/Intermediate Cross Piece (FCP/ICP) of the refrigerators. The reason of the

unnecessary bending is unknown, which is effecting the quality of the concerned product. The

sales department has observed the increase in complaints that the silicon, being filled in the

gaps, turns pale yellow after some period of time which badly affects the aesthetics of the

product. Due to which the goodwill of the brand is facing a negative effect and the company

cannot afford to ignore this defect.

Significant gaps have been observed in FCP/ICP of Refrigerator, due to which an additiona l

cost is occurring in the form of Silicon filling in those gaps and also the aesthetics of the product

is badly affected.

The goal of this project is to detect the critical product which is mainly affecting the revenue

and then identify the root cause of the above defect by using Six Sigma tools and techniques

and eliminate the defect with the help of Six Sigma tools.

After using SIX SIGMA tools and techniques we have detected some causes that were affecting

the product aesthetics by causing the FCP/ICP bend and causing the company to pay extra to

overcome those issues. The root causes of the defect were mainly concentrated at the foaming

station where they use a huge mold to hold the refrigerator assembly while injecting the foam

and that’s where the problems were arising from.

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ACKNOWLEDGEMENT

We wish to acknowledge and thank Chairman Industrial & Manufacturing Department, Dr.

Amir Iqbal and Final year projects coordinator, Mr. Ali Zulqarnain, for giving us an

opportunity to apply the theoretical knowledge which we have studied in books, in actual

industrial environment. It is in our best interest to understand the practical issues in real time

situation and this project has given us an excellent opportunity to excel our skills in the

Quality Control management side of our studies. Our sincere gratitude also extended to our

internal project advisors Miss Rabia Siddiqui and once again Mr.Ali Zulqarnain for guiding

us in this project. We would also like to thank our External Advisor Mr. Tahir Bukhari for

approving this project and giving us a chance to visit Dawlance Private Limited to work on

our project, and guiding us throughout. We would also like to acknowledge Mr. Yahya

Hafeez, Mr. Nasir of Dawlance Private Limited for guiding us in this project. The knowledge

delivered by our highly qualified teachers and their cooperation is warmly acknowledged

especially the teacher who taught us the subject ‘Industrial Quality Control’ Miss Rabia

Siddiqui.

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TABLE OF CONTENTS

Chapter No. Title Page No.

1. Refrigerator Industries In Pakistan

1.1 Orient

1.2 Haier

1.3 Waves Cool Industries

1.4 Pell

10

10

10

10

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2. About Dawlance Private Limited

2.1 Vision Statement

2.2 Mission statement

2.3 Marketing strategies

2.3.1 Product strategies

2.3.2 Pricing strategies

2.3.3 Promotion strategies

2.3.4 Product Life cycle

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12

12

12

13

13

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3. Six Sigma

3.1 Six Sigma 3.2 Six Sigma Methodology

3.3 DMAIC 3.3.1 Define Phase 3.3.2 Measure Phase

3.3.3 Analyze Phase 3.3.4 Improve Phase

3.3.5 Control Phase

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14 14

15 16 17

18 20

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4 Application Of Six Sigma At Dawlance

4.1 Define Phase

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22

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4.1.1 Goal 4.1.2 Steps 4.1.3 Tools

4.1.4 Problem Statement 4.1.5 Goal Statement

4.1.5.1 Specific Issue to Resolve 4.1.5.2 Specific Product to Deal With 4.1.5.3 Specific Stations to Concentrate On

4.1.6 Project Charter 4.1.7 SIPOC

4.1.7.1 Purpose Of SIPOC 4.1.7.2 SIPOC Tells Us About 4.1.7.3 SIPOC Of The Process

4.1.8 VOCs 4.1.8.1 Who is a Customer

4.1.8.2 Types Of Customer 4.1.8.2.1 Internal 4.1.8.2.2 External

4.1.8.3 Identification Of VOCs 4.1.8.4 Customer Requirements

4.1.8.4.1 CTQs 4.1.8.4.2 CTCs 4.1.8.4.3 CTDs

4.1.8.5 CTQ Issues 4.2 Measure Phase

4.2.1 Goal 4.2.2 Steps 4.2.3 Tools

4.2.4 Data Collection Plan 4.2.5 MSA

4.2.5.1 Sources Of Variation In MSA 4.2.5.2 Total Variation 4.2.5.3 Gage R & R Relationships

4.2.5.4 Acceptance Guidance 4.2.5.5 Key Components Of MSA

4.2.5.6 Gage R & R Data Collection Sheet 4.2.5.7 Conclusion

4.2.6 Use Of Quality Tools

4.2.6.1 Histogram 4.2.7 Process Sigma Level Calculation

4.2.7.1 Six Sigma Metrics 4.2.7.2 Nomenclature 4.2.7.3 Basic Relationships

4.2.7.4 DPMO Calculations 4.2.7.5 Quality Level Calculations

4.2.7.6 Yield 4.2.7.7 Yield Relationships 4.2.7.8 Throughput Yield Calculations

4.2.8 Process Capability Analysis 4.2.8.1 Capability Indices

22 22 22

23 25

26 26 26

27 28

28 28 28

30 30

30 30 30

30 31

31 31 31

31 31

31 31 32

32 33

33 33 33

34 34

35 36 37

37 38

38 38 38

39 39

39 40 40

41 42

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4.2.8.1.1 Short Term Capability Indices 4.2.8.1.2 Long Term Capability Indices

4.2.8.2General Guidelines

4.2.8.3 Process Capability Calculations 4.2.8.3.1 Process Data

4.2.8.3.2 Capability (Actual) 4.2.8.3.3 Capability (Potential)

4.2.8.4 Conclusion

4.3 Analyze Phase

4.3.1 Goal

4.3.2 Steps 4.3.3 Tools 4.3.4 Pareto Analysis

4.3.4.1 Determination Of Critical Model 4.3.4.1.1 Data Sheet

4.3.4.1.2 Conclusion 4.3.4.2 Determination Of Critical Defects

4.3.4.2.1 Defects Data Sheet

4.3.4.2.2 Conclusion 4.3.5 FMEA

4.3.5.1 Objectives Of FMEA 4.3.5.2 Process FMEA 4.3.5.3 Conclusion

4.3.5.4 Tables And Standards Used In FMEA 4.3.6 Cause And Effect Analysis

4.4 Improve Phase

4.4.1 Goal 4.4.2 Steps

4.4.3 Tools 4.4.4 FMEA (Controlled)

4.4.4.1 Conclusion 4.4.5 DOE

4.4.5.1 Experiment Design Guidelines

4.4.5.2 Experiment Design Process 4.4.5.3 Problems Faced by The Team In DOE

4.5 Control Phase

4.5.1 Goals 4.5.2 Steps

4.5.3 Tools 4.5.4 Control Plan

4.5.5 Control Charts 4.5.5.1 Basic Principles 4.5.5.2 Errors In Making Inference From C-charts

4.5.5.2.1 Type-I Error 4.5.5.2.2 Type-II Error

4.5.5.3 Analysis of Pattern In Control Chart 4.5.5.3.1 Western Electric Rule

4.5.5.4 Control Charts For The Current Process

4.5.5.4.1 Xbar-R Chart 4.5.5.4.2 Xbar-S Chart

42 43 43

44 45

45 46 46

46 46

46 48 48

48 50

51 52 53

54 54

54 54 55

56 58

59 59 59

59 59

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61 62

62 62 62

62 62

64 64 64

64 64

65 65 65

65 66

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5 Recommendations

5.1 Supplier Quality Control

5.2 Inventory 5.3 Spot Welding Department 5.4 Pre-Foaming

5.5 Foaming Department 5.6 Engineering Department

68 68

68 68 70

70 71

REFERECNES: 72

APPENDICES: 73

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LIST OF FIGURES

Table No.

Description

Page No.

1.

2.

3.

4.

5.

6.

7.

8.

9.

10.

11.

12.

DMAIC Cycle

Define Phase

Measure Phase

Analyze Phase

Improve Phase

Control Phase

Model Ref-9122/9144 (Drawing)

Gap b/w body profile and ICP

Perfectly fitted ICP with no gap

Design of Experiment

Spot Welding Standard Parameters

Foaming Mold In Open Condition

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8

9

10

11

12

15

16

17

52

60

62

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LIST OF TABLES

Table No. Description Page No.

1.

2.

3.

4.

5.

6.

7.

8.

9.

Sigma Level

Process capability

Process Cp Range

FCP Bend Data Sheet

Production Data Sheet

Defects Data Sheet

Severity Ranking

Failure Rate Ranking

Failure Detection Rating

33

33

35

38

47

48

48

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CHAPTER 1

REFRIGERATOR INDUSTRIES IN PAKISTAN

There are different home appliance companies in Pakistan of which many are also

manufacturers of refrigerators.

Some of the large scale leading companies that manufacture refrigerators are:

1.1 ORIENT:

Orient Group of Companies has been on the forefront of design and development, by

coming up with new products and increasing its presence in all its featured markets.

Established in Lahore in1957, today the Orient Group of Companies is one of the largest

consumer goods companies of Pakistan. Orients products have proven themselves in

functional performance parameters set by international industry experts. With the vision

to become leaders of the industry.

1.2 HAIER:

Haier is a leading global brand that recognizes and respects the realities and

circumstances of its customers and responds to these by rewarding them with inspiring

solutions they can always rely on. Haier comes from the belief that progress lies in

continued technological advancement in order to make customers’ lives easier, more

efficient and more productive and it will continue making all the efforts to excel in the

market. As Haier is moving towards Eco-Life which will be very effective in making

customers’ life more convenient in terms of products usage & efficiency. The idea of

Eco-Life will reflect the Haier promise of ‘Smarter Life, Better Planet for the masses in

Pakistan.

1.3 WAVES COOL INDUSTRIES:

Waves Cool Industries (Pvt.) Limited was established in 1973 and grew to a leading

Home Appliances manufacturing Company in Pakistan, in a very short span of time. This

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was achieved by the tireless efforts of our devoted Management, highly motivated

professionals and dedicated team work, committed to excel in the quality and services.

Waves Cool Industries (Pvt.) Limited, has highly skilled professionals, responding

rapidly to the market needs. With the most modern and high-tech CAD manufacturing

facilities, our products capture over 80% of the local market for Refrigerators, Deep

Freezers, Air Conditioners and other home appliances. The company manufactures

Refrigerators, Deep Freezers, Air Conditioners, Washing Machines, Microwave Ovens

and many other quality home appliances, with the production ratio exceeding the overall

production of Pakistan’s appliances manufacturers.

1.4 PEL:

The manufacturing of refrigerators started in 1986-87 in technical collaboration with M/s

IAR-SILTAL of Italy. Like the air conditioners, PEL's refrigerators are also in great

demand. Today, PEL Crystal has 30% market share.

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

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

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CHAPTER 2

ABOUT DAWLANCE PRIVATE LIMITED

Dawlance is widely regarded as one of the premiere home appliances companies in Pakistan,

with a history, spanning more than 3 decades. The company initiated its operations in 1980,

with the production of refrigerators.

Today, besides refrigerators, Dawlance is producing washing machines, chest freezers,

vertical freezers, split air conditioners and microwave ovens. Over the years, Dawlance has

not only developed the largest dealers’ network, but has also established the largest after-

sales service set-up across Pakistan.

It is the 3rd most favorite brand in Pakistan out of a total of 3500 brands; and is also amongst

the Top 2 ‘Top of the Mind' (TOM) brands in all durable product categories. Through

independent research carried out, it was determined that every household having household

appliances has a Dawlance product, owing to its ever-increasing credibility, reliability and

innovation, surpassing all the other electronic brands in Pakistan.

It’s this ethos of ‘reliability’ which is the differentiating characteristic of Dawlance and is

permeated within all functions of the organization.

Dawlance has the largest set up with respect to manufacturing capabilities, retail outlets,

service centers and distributors. Throughout its 34 years, the company has maintained

superior quality standards and can proudly state it is also the first Pakistani company to have

been awarded the ISO 9001, ISO 14001 and OHSAS 18001.

With 3 factories, 16 sales branches, 26 company-owned after sales customer service centers,

165 affiliated after-sales customer service centers, over 800 sales and service staff and more

than 4000 employees, Dawlance has come a long way.

2.1 VISION STATEMENT:

To become a global player by practicing Reliability: Make Pakistan Proud of Us!

2.2 MISSION STATEMENT:

To promote reliability in everything we do in the field of Household Appliances.

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2.3 MARKETING STRATEGIES:

2.3.1 PRODUCT STRATEGY:

The objective of Dawlance is to provide electronic appliances to all people

who fall in lower middle, middle, and upper middle class in this country such that most of the families should have refrigera tors in their home because they enhance

better quality of life. Dawlance has got products, which are as per internat iona l standards and carry all the basic features, which need in any such type of appliances. Dawlance believe that whatever they provide to their customers

should be durable and reliable. All the products, which Dawlance market, are durable enough and customer can keep on using them for quite many years

without any problem. It provides its refrigerators, 3 years compressor guarantee and1 year chest freezer, and free service in spare parts under normal use.

2.3.2 PRICING STRATEGY:

Dawlance has got a policy that their all product price should be the same in all cities and town in Pakistan market. Dawlance bear freight cost and make their product available to their dealers irrespective of where they are located. For this, they

give uniform margin to their dealers irrespective of whether he is big or small. Dawlance consider pricing as one of an important element of marketing mix. I t be lieves tha t

the ir re ta il p r ices should be unifo r m a ll ove r the country irrespective of whether customers buy from Peshawar or Karachi. In order to mainta in a uniform price all over the country, Dawlance bears transportation charges

and make the product available at cost price at dealer premises.

2.3.3 PROMOTION STRATEGY:

Dawlance promotion budget is around 1.75% of their turnover. 40% spending of their

budget is Print Media, 20% goes on TV, 20% on outdoor activity and balance 20% on Sales Promotion activity. They believe that print media and outdoor

activity help them to reach to their target customer. Due to satellite transmission and having multi-channels, it does not pay one unless you have very huge budget to spend on this media. On promotion, their spending is more on consumer

incentive schemes. Since it pay them and there is direct relationship between sales and consumer. Further, it gives customer a direct benefit in shape of price

reduction.

2.3.4 PRODUCT LIFE CYCLE:

Dawlance is ISO 9000 and among its mission statement, it is one of their mission to

provide quality products to their customers. Therefore they ensure that every product,

which is delivered from their factory, must go through rigorous quality check. So that

only perfect products, free from any defects is delivered to their customers.

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CHAPTER 3

SIX SIGMA

3.1 SIX SIGMA

Six Sigma is a rigorous, focused and highly effective implementation of proven quality

principles and techniques. Incorporating elements from the work of many quality pioneers,

Six Sigma aims for virtually error free business performance. A company’s performance is

measured by the sigma level of their business processes.

Six Sigma takes a handful of proven methods and trains a small cadre of in-house technical

leaders, known as Six Sigma Black Belts, to a high level of proficiency in the application of

these techniques.

Six Sigma relies on tried and true methods that have been around for decades. In fact, Six

Sigma discards a great deal of the complexity that characterized Total Quality Management

(TQM). Six Sigma is about helping the organization make more money by improving

customer value and efficiency.

To link this objective of Six Sigma with quality requires a new definition of quality. Six

Sigma focuses on improving quality (i.e., reducing waste) by helping organizations produce

products and services better, faster and cheaper. There is a direct correspondence between

quality levels and “sigma levels” of performance. The Six Sigma philosophy focuses the

attention of everyone on the stakeholders for whom the enterprise exists. It is a cause-and-

effect mentality.

3.2 SIX SIGMA METHODOLOGY:

For the most part, these are the same tools used by the quality profession and applied

statisticians for decades. Six Sigma puts some new twists on these traditional tools:

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1. They are taught in the context of a well-defined improvement model known as DMAIC

(see below). Computers are used intensively.

2. They are applied at once on real projects designed to deliver tangible results for an

identified stakeholder.

3. Items 1and 2 are integrated via an intensive training regimen that is provided to full-

time change agents who work on projects while they are being trained.

The tools of Six Sigma are most often applied within a simple performance improvement

model known as Define-Measure-Analyze-Improve-Control, or DMAIC.

3.3 DMAIC:

DMAIC is such an integral part of Six Sigma. It provides a useful framework for conducting

Six Sigma projects. DMAIC is sometimes even used to create a ‘‘gated process’’ for project

control. That is, criteria for completing a particular phase are defined and projects reviewed

to determine if all of the criteria have been met. If so, then the gate (e.g., Define) is ‘‘closed.’’

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Figure 1

3.3.1 Define Phase:

Define the goals of the improvement activity. The most important goals are obtained from

customers. At the top level the goals will be the strategic objectives of the organization, such

as greater customer loyalty, a higher ROI or increased market share, or greater employee

satisfaction.

In the Define phase you’ll confirm the preliminary decisions you made about the reasons for

tackling the problem you identified and go into more detail about the purpose, objectives, and

scope of your project. You’ll also collect data on the process and your customers and identify

the project results you want. In other words, by the end of this phase, you will have

effectively defined your project. By now, you should have chosen your first project and you

should be ready to begin moving into DMAIC.

The following outline delineates the steps in the Define process.

1. Identify the problems in your process: This is a preliminary process, to provide some

initial focus.

2. Identify the process owner/sponsor: The project Sponsor is often played by the process

owner—the manager or supervisor who is closest to the process you are improving.

3. Begin the project charter: The project charter is a document that evolves over the

course of a Six Sigma project.

4. Assemble the project team.

5. Build a RACI chart: to determine how involved each member will be in the decision-

making process. The best way to do that is to create a system chart according to the

RACI.

6. Collect customer data.

7. Translate VOC (Voice of Customer) into CTQs

8. Develop problem statements.

9. Establish project metrics.

10. Focus on the vital few factors.

11. Identify necessary resources.

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12. Create a project plan.

13. Conduct a Phase-Gate Review.

Figure 2 (Define phase)

3.3.2 The Measure Phase:

Measure the existing system. Establish valid and reliable metrics to help monitor progress

towards the goals defined at the previous step.

Companies need to validate measurements for data to be used in making decisions. The

Measure phase ensures you have a good working measurement system, so you can trust the

data that you are going to analyze.

The Measure Phase Of Six Sigma Has Two Components:

1. Validate the measurement system (making sure you can trust the numbers): The goal of

this first part of the Measure phase is to make sure you have valid data. What does it

mean to be valid?

The point is not to inspect, but expect.

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2. Collect new data.

A technique for determining the validity of a measurement system according to four essential

criteria: accuracy, repeatability, reproducibility, and stability (accuracy, repeatability, and

reproducibility over time).

The steps required in the Measure phase:

1. Select product or process CTQ characteristics; e.g., CTQ Y’s.

2. Define performance standards for Y’s.

3. Identify X’s.

4. Validate the measurement system for Y’s and X’s.

5. Collect new data.

6. Establish process capability (sigma level) for creating Y.

7. Conduct a phase-gate review.

Figure 3 (Measure phase)

3.3.3 Analyze Phase:

Analyze the system to identify ways to eliminate the gap between the current performance of

the system or process and the desired goal.

The Analyze phase helps us to determine what is vital and what is trivial.

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Begin by determining the current baseline. Use exploratory and descriptive data analysis to

help you understand the data. Use statistical tools to guide the analysis.

The Analyze deliverable is the choice of the high level design concept to be created. The

design is ‘‘best’’ in the sense that it best meets the CTQs.

In the Analyze phase we determine which factors are causing the problems in your critical

metrics. When you analyze the data collected during the Measure phase, it is important to

estimate the limits within which we can be confident that the small group sample statistics

like mean and standard deviation are really telling us about differences in the total

population.

Hypothesis testing (comparisons) is the Analyze phase tool that leads us to the vital few

variables.

Once customers have made their demands known in the Define/Measure phase, it is

important that these be converted into design requirements and specifications. The term

‘‘translation’’ is used to describe this process because the activity literally involves

interpreting the words in one language (the customer’s) into those of another (the employee).

Figure 4 (Analyze phase)

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3.3.4 Improve Phase:

In the Improve phase we are establishing the relationship between inputs and outputs. The

simple way of doing this is a graphical method of correlation the Improve phase is about

good judgment and using data to derive solutions.(1)

Improve the system. Be creative in finding new ways to do things better, cheaper, or faster.

Use project management and other planning and management tools to implement the new

approach. Use statistical methods to validate the improvement.

Correlation analysis determines the extent to which values of two quantitative variables are

proportional to each other and expresses it in terms of a correlation coefficient. Proportional

means linearly related; that is, the correlation is high if it can be approximated by a straight

line (sloped upwards or downwards). Correlation measures the degree of linearity between

two variables.) The value of the correlation coefficient is independent of the specific

measurement units used.

Figure 5 (Improve phase)

3.3.5 Control Phase:

The main methods used in the Control phase are statistical process control (SPC) and mistake

proofing. These methods complete the cycle of finding the controls for the solution and, more

importantly, maintaining the control of the solution. You cannot assume that training or

changing policies or procedures will be adequate to achieve control.

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You cannot skip or get around the Control phase unless you eliminate the defect. There are

many situations in which a Six Sigma team finds that no control is necessary because the

team made the cause of the defect completely go away by setting and maintaining the right

inputs.

The Control phase ensures the new process conditions are documented and monitored via

process control methods. After a settling-in period, the process capability should be

reassessed. Depending upon the outcomes of such a follow-on analysis, it may be necessary

to revisit one or more of the preceding phases.

The basic steps in the Control phase to serve as a guideline for working with control charts:

1. Select the variable to chart.

2. Select the type of control chart to use.

3. Determine rational subgroup size and sampling interval/frequency.

4. Determine measurement methods and criteria.

5. Calculate the parameters of the control chart.

6. Develop a control plan.

7. Train the people and use the charts.

8. Conduct a phase-gate review.

When a process is in control, it means only that the performance is stable and predictable. It

does not mean that the performance is acceptable to you or your customers. If the average of

an in-control process is off target from where you want it to be or the control limits are too

far apart (meaning there is too much common cause variation), your only course of action is

to make fundamental changes in the process. You need to redesign the process in some way

so that there is a different mix of common cause factors.

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Figure 6 (Control phase)

CHAPTER 4


4.1 DEFINE PHASE:

4.1.1 Goal of This Phase:

The goal of define phase is to:

Identify a process to improve and develop a specific Six Sigma project

We are determining exactly what we intend to work on and estimating the impact to

the business.

At the completion of the define phase we should have a description of the process

defect that is creating waste for the business.

4.1.2 Steps of This Phase:

The typical steps that we took in this phase were:

Define the problem by developing the “problem statement”

Define the goal by developing the “goal statement”

Define the process by developing the “process maps”

Define the customer by defining their “requirements”

4.1.3 Tools Used In This Phase:

The tools that we have used in this phase are:

Project charter

Process map

SIPOC

VOC translation into CTQ’s

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4.1.4 Problem Statement:

The problem we have been given to solve and implement the remedial actions was that, at the

end of a foaming process we observed significant gaps between the body profile and

Intermediate Cross Piece (ICP) and the same with Front Cross Piece (FCP) that was caused

mainly by the deshape or bending of these two components (i.e. ICP and FCP).

To overcome these problems company must have to fill those gaps by using Silicon filler

between the gaps because if they don’t fill the gaps, refrigerator door won’t be aligned with

the body and hence the product won’t serve its intended purpose.

The major problem with the silicon filler are:

It is an imported item and hence it costs high.

With the passage of time it turns pale yellow that affects the aesthetics of the product.

Company had to engage a separate worker for that.

Silicon filling takes sometime which badly affects the cycle time of the process.

As a result of above problems the company was paying the cost of poor quality (CPQ) in

order to save the company’s goodwill and maintain the product’s quality.

Attached drawings shows the physical dimensions overlook of the product in order for a

reader to understand the problem more clearly:

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Figure 7 (REF-9122/9144)

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Figure 8 (Gap b/w body profile and ICP)

4.1.5 Goal Statement:

The goal of this project is to identify the root cause of the defect by using six sigma tools and

techniques and then take measures to remove or reduce that defect.

Hence by reducing the defects means reducing the cost of the product by eliminating the cost

of poor quality that the company is paying. Also reducing the variability of the processes in

order to improve the quality of the product.

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4.1.5.1 Specific Issue to Resolve: The specific issue given to us to resolve was reducing the

FCP/ICP bend and hence the gap between the bodies profile and FCP/ICP. Although the

scope of our project includes: identifying all the issues that are threat to the quality, so in

order to go with the project scope we’ll be obeying six sigma methodology. We’ll consider

all the quality related issues while carrying out cause and effect analysis.

4.1.5.2 Specific Product to Deal With: The specific products given to us to deal with was

the two refrigerator models REF-9122 and REF-9144. As far as the physical design is

concern the two models use the same ICP and FCPs. Although while carrying out the Pareto

analysis we’ll consider all the major products that were produced during our study period.

4.1.5.3 Specific Station/Departments to Concentrate On: The specific departments already

given to us to concentrate on includes the following:

Sheet metal department

Pre-Foaming and

Foaming

Figure 9 (Perfectly Fitted ICP with no gap)

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4.1.6 Project Charter:

START END

SIGN

TARGET Current Sigma Level TARGET

BUSSINESS CASE: ESTIMATED SAVING EXPECTED

COST

BASIC SCHEDULE:

3

Scope Statement

PROBLEM STATEMENT:

MEASUREABLE GOALSREWORK REDUCTION

UNIT: PERCENTAGE

CURRENT

NAME

Tarteel Ahmed

Usman Ghani

Raffay Bin Rauf

M.Shahbaz Baig

MBB

BLACK BELT

Mr. Ali ZulqarnainGOAL STATEMENT:

PROJECT CHARTER14-01-14 28-10-14

DOCUMENT NO:

RESPONCES

PROJECT SPONSOR Dawlance

TE

AM

ME

MB

ER

S

Significant gaps have been observed in FCP/ICP of Refrigerator, due to which an additional cost is occurring in the form of Silicon filling in those gaps and also the aesthetics of the product is badly affected.

Significant improvements will reduce the gaps up to the company’s standard. Our objective is to identify the root cause for the bend and remove this defect by using Six Sigma toolsand techniques.

PE

RIO

D

Dawlance is the 7th most Favorite brand in Pakistan,out of 3500 brands.Research revealed that Dawlance is in Every 2nd house hold in Pakistan,out of those house holds which have appliances. Dawlance is considered to be the most ‘Reliable’ & ‘Innovative’ brand among all home appliance brands in Pakistan.The issue which has been highlighted in this project is the silicon filler , which is an expensive imported item , and is being used to fill the gaps which are occurring due to bending of FCP/ICP of the refrigerators.The reason of the unnecessary bending is unknown, which is effecting the quality of the concerned product. The sales department reported that the silicon, being filled in the bend gaps, turns pale yellow after some period of time which effects the aesthetics of the product. Due to which the goodwill of the brand is facing a negative effect and the company can not afford to ignore this defect .

Analyze the bend status at different stations, mainly on spot welding, pre-foaming and foaming.Identify root causes of the bend.Resolve the issue using Six Sigma tools and techniques.Eliminate the usage of silicon between the gaps.

29

4.1.7 Supplier Input Process Output Customer (SIPOC):

It is a high level process map that tells the team about the routing of the concerned product.

4.1.7.1 Purpose of SIPOC: Includes the following:

A tool to identify all relevant elements of a process.

It helps to understand a complex process better.

It is the graphic display of steps, events and operations that constitute a process.

4.1.7.2 SIPOC tells us About: It tells the team about the following:

Where does the process START and END?

What are the major steps in the process (P)?

What are the primary process inputs (I) and outputs (O)?

Who are the key customers (C) of the process (Internal and External)?

Who are the key suppliers (S) of the process (Internal and External)?

What are the requirements of the customer?

4.1.7.3 SIPOC of the Process: The SIPOC we have created for the process is oriented

around only those processes which are critical processes at the critical stations where process

owner thinks the defects are coming from. It highlights only those stations that includes the

handling of FCP/ICP.

30

SUPPLIER (S) INPUT (I) PROCESS (P) OUTPUT (O) CUTOMER (C)

Foaming Completely Foamed Cabinet

QUALITY CONTROL

Defected or OK Product Refrigerator Assembly

Completely Cabinet Ready For

Assebmly Shop

Pre-foaming

PHASE 2: of Pre-foaming

Fully Painted Body

Cabinet fitted with PP-sheet

at the back

Complete Pre-foamed cabinet

Ready for FOAMING FOAMING

Complete refrigerator frame

ready for Paint Paint Shop

complete Ref Cabinet

Fully Painted Body

Cabinet Fitted with PP-sheet at the back

SIPOC CHART

Pre-foaming

Sheet Metal

SQA

Spot Welding

Paint Shop

PHASE 1: of Pre-foaming

Pre-Foamed cabinet

Cabinet

FCP, ICP, Z-bottom, Compressor support

Joining of FCP, ICP, Z-bottom and Compressor support by SPOT WELDING

Painting

(PHASE 1) Fitting of PP sheet

(PHASE 2) Taping (to avoid foam leakage), Groomets fixing, Profile fixing, Fitting Of ANTI-MOISTURE TUBE, adjustment and Fixing of

Freezer assy and Ref lining

FOAMING

INSPECTION (Faom short run test and FCP/ICP bend Check)

Rework

Ref Assembly

DefectedOK

31

4.1.8 The Voices of Customers (VOCs):

4.1.8.1 Who Is a Customer? : One who is paying for your services or products OR a person

who buys goods or services.

4.1.8.2 Types of Customers:

4.1.8.2.1 Internal: Anyone in the company who is affected by product or services as it is

being generated.

4.1.8.2.2 External: Are not the part of the organization but are impacted by it.

4.1.8.3 Identification of VOCs:

S.NO CUSTOMER

NAME

TYPE VOICE OF CUSTOMER

(VOC)

1. Refrigerator

Assembly

Internal Perfectly aligned door

2. Quality Control

(QC) Department

Internal No bend between

Intermediate Cross

Piece(ICP) and Body profile

3. Distributer External

(intermediate)

No service call rate (SCR)

4. User External

(End)

Better aesthetics

32

4.1.8.4 Customer Requirements: Important Customer Key Process Outputs (KPOV)

categories are sometimes classified with regard to their area of impact into three major

dimensions:

4.1.8.4.1 Critical to Quality: e.g. Physical dimensions, surface finish, taste etc.

4.1.8.4.2 Critical to Cost: Deals exclusively with the impact of cost on the customer.(N/A)

4.1.8.4.3 Critical to Delivery: Represents those customers with stated needs regarding

delivery. (N/A)

4.1.8.5 Critical to Quality Issues (CTQs):

Better First Past Yield (FPY)

No re-work cost

o No silicon cost

o No labor cost

o No cost due to Delay

No bend between Intermediate Cross Piece (ICP) and body profile.

4.2 MEASURE PHASE:


The goal of measure phase is to:

Determine the start point or baseline of the process

Find clues to understand the root cause of the problem in the process.


Typical steps that we took in this phase includes:

33

Determine how the process currently performs.

Look for what might be causing problems.

Create a plan to collect the data.

Ensure your data is reliable


The tools that we used in this phase includes:

Data collection plan.

Measurement System Analysis (MSA).

QC tools.(Histogram)

Process Sigma level.

Process capability analysis.

4.2.4 Data Collection Plan:

FREQUENCY WHEN WHERE

Refrigerator's cabinet size Discrete

Inspection of outer dimensions of

refrigerator's cabinet by using measuring

tape. Allowable tolerance is ±2mm on

each dimension. The cabinet is examined

after undercoat and paint are applied and

dried.

Team members

No differences in the dimensions

of the cabinet is recognizable. All

dimensions should be under the

given tolerance

MEASUREMENT DATA TYPE OPERATIONAL DEFINITION RESPONSIBLE Decision CRITERIA

Foaming station

30 units At appropriate timePre-foaming

Department

Gap between body profile and

ICP (Intermediate cross piece)Discrete

Inspection of the Gap between body

profile and ICP by using Filler gauge.

Allowable tolerance is ±2mm. The

Refrigerator Cabinet is examined after the

pre-foaming station.

Team members

No cabinet is recognizable in

which the gap between the body

profile and ICP exceeds to the

given tolerance.

30 units At appropriate time

34

4.2.5 Measurement System Analysis:

The purpose of measurement system analysis is:

To determine if a measurement system can generate accurate data.

If accuracy is adequate to achieve the measuring objectives.

4.2.5.1 Sources of Variation in the Measurement System:

Intrinsic (Inherent) OR Measurement System Variation (б2Gage) or (GRR)

o Accuracy

o Precision

Variation due to gage (i.e. repeatability) (б2repeat) or (EV)

Variation due to operator (i.e. reproducibility) (б2repro) or (AV)

Extrinsic OR part to part OR Process/Product variation (б2part-part ) or (PV)

4.2.5.2 Total Variation:

б2total = б2

part-part + б2Gage

Where;

б2Gage = б2

repeat + б2reproduce

4.2.5.3 Gage R & R Relationships:

This section describes some AIAG (American International Automotive Group) relationships

and expands previous GRR relationships.

%PV = 100(PV/TV)

%EV = 100(EV/TV)

%AV = 100(AV/TV)

%GRR = 100(GRR/TV)

35

4.2.5.4 Acceptance Guidance: In general (according to AIAG) if %GRR is:

Less than 10%, the measurement system is considered ACCEPTABLE.

Between 10%-30% inclusive, the measurement system is MARGINAL.

Greater than 30%, the measurement system is considered INADEQUATE.

4.2.5.5 Key Components Of Measurement System:

Measurement instrument.

Appraiser(s) also known as Operators.

Methods or procedures of conducting measurement.

Environment.

4.2.5.6 Gage R & R Data Collection Sheet:

The sheet attached to the next page is designed according to the standards of AIAG

(Automotive Industry Action Group).

36

Gage R & R Data Collection Sheet-AIAG Method:

Appraisers 1 2 3 4 5 6 7 8 9 10 Average Appraiser

A1 2 2 2 2 2 2 2 2 1.998 2 1.998 A1

A2 2 2 2 2 1.998 2 2 2 2 2 1.998 A2

A3 2 2 2 2 2 2 2 2 1.998 2 1.998 A3

Average A 2 2 2 2 1.999 2 2 2 1.999 2 1.9998 X-bar(A)

Range A 0 0 0 0 0.002 0 0 0 0.002 0 0.0004 R-bar(A)

B1 2 2 2 2 2 2 2 2 2 2 2 B1

B2 2 2 2 2 2 2 1.998 2 2 2 1.999 B2

B3 2 2 2 2 2 2 2 1.998 2 2 1.999 B3

Average B 2 2 2 2 2 2 1.999 1.999 2 2 1.9998 X-bar(B)

Range B 0 0 0 0 0 0 0.002 0.002 0 0 0.0004 R-bar(B)

C1 2 2 2 1.998 2 2 2 2 2 2 1.999 C1

C2 2 2 2 1.998 2 2 2 2 2 2 1.999 C2

C3 2 2 2 2 2 2 2 2 2 2 2 C3

Average C 2 2 2 1.999 2 2 2 2 2 2 1.9999 X-bar{C}

Range C 0 0 0 0.002 0 0 0 0 0 0 0.0002 R-bar{C} Part Average 2 2 2 1.999 1.999 1.999 1.999 1.999 1.999 2 1.999 X-bar-bar(part)

Max. part average - Min. part average = 2 - 1.999 0.001 R(part)

(R-bar[A]+R-bar[B]+R-bar[C])/No. of Appraisers = (0.0009+0.0004+0.0002)/3 0.0003 R-bar-bar

X-bar(Diff) = MAX(X-bar[A], X-bar[B], X-bar[C]) - MIN(X-bar[A], X-bar[B], X-bar[C]) 0.0001 X-bar(Diff)

UCL[R] = D4*R-bar-bar = 2.574*0.0003 = 0.000858

LCL[R] = D3*R-bar-bar = 0*0.0005 = 0

PART

37

Gage R & R Report-AIAG Method:

4.2.5.6 Conclusion:

As % gage R & R is between 10% to 30% therefore measurement system is considered as

marginal.

Gage Repeatability and Reproducibility

Part Name: FCP Gage Name: Feeler Gage Date: Feb 22nd, 2014

Characteristics: Gage No. N/A Performed by: Six Sigma Team

Specifications: Gage Type: Feeler Gage

From Data Check Sheet R-bar-bar = 0.0003 X-barDIFF=0.0001 RPART=0.001

Measurement Unit Analysis

Repeatability – Equipment Variation (EV) EV = R-bar-bar * K1 = 0.0003* 0.5908 = 0.000132

% EV = (EV/TV)*100 = 36.36%

Reproducibility – Appraiser Variation (AV) AV = {(X-barDIFF * K2)2 – (EV2 / (n*r)}1/2

= {(0.0001*0.5231)2 – (0.0001772/10*3)}1/2 = 0.0000411

%AV = (AV/TV)*100 = 11.3%

Gage Repeatability and Reproducibility GRR = (EV2+AV2)1/2

= (0.0001322 + 0.00004112)1/2 = 0.000121

%GRR = (GRR/TV)*100 = 30%

Part Variation PV = Rpart * K3 = (0.001*0.3146) = 0.0003146

%PV = (PV/TV)*100 = 83.22%

Total Variation TV = (GRR2+PV2)1/2

= 0.000378

38

4.2.6 Use of Quality Tools:

4.2.6.1 Histogram:

The Histogram is applicable here as per the requirement. We use following continuous data

in millimeters that was taken by the measurement of bend between refrigerator body profile

and FCP. The data used in this Histogram is shown in Table 4.

3.22.82.42.01 .61 .20.8

1 2

1 0

8

6

4

2

0

Mean 1 .91 3

StDev 0.5453

N 50

Bend (mm)

Fre

qu

en

cy

Bend TrendNormal

39

4.2.7 Process Sigma Level Calculation:

4.2.7.1 Six Sigma Metrics: We were provided with the production and defect data of three

months (i.e. from Jan, 14 to Apr, 14) and so we calculated the sigma quality level with those

three months data.

Total products (Refrigerator models) given to us were actually four but unfortunately one of

them didn’t produced at all during those three months, so we analyzed the data about just

three types of products, as per the Internals’ and External’s guidance.

4.2.7.2 Nomenclature:

Number of operation steps = m

Defects = D

Units = U

Opportunities for a defect = O

Yield = Y

4.2.7.3 Basic Relationships:

Total opportunities: TOP = U x O

Defects per Unit: DPU = D/U

Defects per Unit Opportunity: DPO = DPU/O = D/U x O

Defects per Million Opportunities: DPMO = DPO x 106

40

4.2.7.4 DPMO Calculations: The data used for this tool was given to us by the company that

is shown in attachment.

Characteristic Defects

Units

Opportunities

Total Opportunities

Defects per Unit

Defects per Total Opportunities

Defects per Million Opportunities

D U O TOP = U*O DPU=D/

U

DPO=D/TOP

DPO=(D/U)*

O

DPMO=DPOx106

9122

2495 7018 133 933394 0.3555143

91

0.002673040 2673.04000

9144

5262 17278 292 5045176 0.304549137

0.001042976 1042.97600

9188

1335 5051 209 1055659 0.264304098

0.001264612 1264.61291

TOATAL 9092 7034229 4980.62891

4.2.7.5 Quality Level Calculation:

Sigma Quality Level = 0.8406 + √29.37 – 2.221 {ln (DPMO)}

= 0.8406 + √29.37 – 2.221 {ln (4980.62891)}

Sigma Quality Level = 4

4.2.7.6 Yield:

Probability of a part made within specifications OR Probability of a part with zero failures.

Yield = e-DPU

Where DPU: Defects per Unit

41

4.2.7.7 Yield Relationships:

Throughput Yield: YTP = e-DPU

Defects per Unit: DPU = -ln (YTP)

Rolled Throughput Yield: YRT = ∏i=1 m (YTPi)

Total Defects per Unit: TDPU = -ln (YRT)

Normalized Yield: Ynorm = m√ YRT

4.2.7.8 Throughput Yield Calculation:

Because of lack of relevant data about the operations performed on the product, we have to

use the Sigma calculator template as given by the Internal.

The table below shows the direct calculations of sigma level (already calculated above) and

throughput yield.

42

Throughput Yield = 0.700812858+0.737455791+0.767740035/3

YTP = 73.53%

Rolled throughput Yield = (0.700812858*0.737455791*0.767740035)

YRT = 39.67%

Normalized Yield = 3√0.396782253

YNO RM = 73.48%

4.2.8 Process Capability Analysis:

Capability analysis numerically compares the voice of process (VoP) to the voice of

customer (VoC).

Defined as the industry benchmark.

Represent 1.5 б shift in process relative to specification target.

Characteristic Defects

Units

Opportunities

Total Opportunities

Defects per Unit

Throughput Yield

D U O TOP = U*O DPU=D/

U YTP = e-DPU

9122

2495 7018 133 933394 0.3555143

91

0.700812858

9144

5262 17278 292 5045176 0.304549137

0.737455791

9188

1335 5051 209 1055659 0.2643040

98

0.767740035

TOATAL 9092 7034229

43

Table 1

4.2.8.1 Capability Indices:

Table 2

4.2.8.1.1 Short-Term Capability Indices:

Cp = (𝐔𝐒𝐋−𝐋𝐒𝐋)

𝟔б (𝐬𝐡𝐨𝐫𝐭)

Sigma

Level

Short-Term

DPMO

Long-Term

DPMO

1 158655.3 691462.5

2 22750.1 308537.5

3 1350 66807

4 31.7 6209.7

5 0.3 232.7

6 0.0 3.4

Process Potential Process Actual

Cp Pp Relates std.dev to tolerance

Cpk Ppk Relates Mean & std.dev to

tolerance

Short-Term

Pooled std.dev “potential”

Performance

Long-Term

Overall std.dev “Actual”

Performance

44

б =𝐑(𝐛𝐚𝐫 )

𝒅𝟐 OR

𝐒(𝐛𝐚𝐫)

𝒄𝟒 }Short Term

Cpk = Min{ Cpk(USL), Cpk(LSL) }

Cpk(USL) = (𝐔𝐒𝐋−µ)

𝟑б (𝐬𝐡𝐨𝐫𝐭)

Cpk(LSL) = (µ−𝐋𝐒𝐋)

𝟑б(𝐬𝐡𝐨𝐫𝐭)

4.2.8.1.2 Long-Term Capability Indices:

Pp = (𝐔𝐒𝐋−𝐋𝐒𝐋)

𝟔б (𝐥𝐨𝐧𝐠)

Ppk = Min{ Ppk(USL), Ppk(LSL) }

Ppk(USL) = (𝐔𝐒𝐋−µ)

𝟑б (𝐥𝐨𝐧𝐠)

Ppk(LSL) = (µ−𝐋𝐒𝐋)

𝟑б(𝐥𝐨𝐧𝐠)

4.2.8.2 General Guidelines:

Cp = capability of process = Voice of client

Voice of process =

Tolerance

Width of distribution

45

Table 3

4.2.8.3 Process Capability Calculations:

The data used for these calculations is shown in Table 4.

Cp OR Pp Process is:

<1.00 Incapable

=1.00 Marginal

>1.00 Capable

46

4.2.8.3.1 Process Data:

LSL = 0

USL = 2.5

Mean (µ) = 1.913

Sample Size (N) = 50

Std.dev (overall) = 0.545326

Std.dev (within) = 0.58392

4.2.8.3.2 Capability (Overall or Actual):

Pp = 0.76

47

Ppk(LSL) = 1.17

Ppk(USL) = 0.36

Ppk = 0.36

4.2.8.3.3 Capability (Potential or Within):

Cp = 0.71

Cpk(LSL) = 1.09

Cpk(USL) = 0.34

Cpk = 0.34

4.2.8.4 Conclusion:

As process capability index (Cp) is found 0.71, so referring to the Table 3 our process is

INCAPABLE of producing the product within the specification limits. That shows that there

must be something going on wrong in the process that needs to be corrected.

So we will take care of that in further improve phase.

4.3 ANALYZE PHASE:


The goal of Analyze phase is to:

Review the data collected in measure phase.

Analyze both the data and process in an effort to narrow down and verify the root

cause of waste and defects.



Closely examine the process.

Visually display the data.

Brain storm potential cause(s) of the problem.

Verify cause(s) of the problem.

48

S.NO FCP BEND (mm)

1 2.20 2 2.61

3 1.15

4 2.80 5 2.65

6 2.30 7 1.79

8 1.68

9 2.46 10 1.38

11 2.59 12 2.15

13 1.05

14 1.30 15 2.35

16 2.15 17 1.17

18 1.20

19 1.95 20 2.60

21 2.30 22 1.90

23 1.80

24 1.22 25 2.04

26 1.23 27 1.96

28 1.26

29 2.00 30 2.51

31 1.23 32 1.09

33 1.23

34 2.50 35 2.58

36 1.88 37 1.14

38 2.22

39 2.40 40 1.92

41 2.14 42 2.39

43 1.34

44 2.44

Table 4

49



Pareto Analysis.

Cause and effect diagram.

Failure Mode Effective Analysis (FMEA).

4.3.4 Pareto Analysis:

In this phase we used Pareto analysis to determine the critical model as well as the critical

defect that was causing the company to pay for the cost of poor quality.

4.3.4.1 To Determine the Critical Model: The data used for this analysis is shown in Table

5. The data that we are using in this analysis is of four months (i.e. from Jan, 14 to Apr, 14).

45 1.13 46 2.44

47 2.47 48 1.81

49 1.28

50 2.27

51

4.3.4.1.1 Production Data Sheet:

Model Quantity

REF 9122 MDS (METALLIC GOLD) 2445

REF 9144 M (PEACH BROWN) 2003

REF 9144 MONO PLUS SS CHECKERED 1153


REF 9144 M (GRAPHITE GREY) 325


REF NR-340-MG (PEARL WHITE) 9188M 156

REF 9107 (BLACK & BLUE) 112

REF 9107 (BLACK & RED) 108

REF 9101 SD (BLACK & RED) 32

REF 9188 M (PEARL WHITE) 29

REF 9106 SD (BLACK AND RED) 4

REF 9106 SD (BLACK AND BLUE) 2





REF 9188 D (METALLIC GOLD) 856



REF 9144 M (2TONE GREY) 521

REF NR-340-DM (METALLIC GOLD) 9188D 316

REF NR-340-MG (PEACH BROWN) 9188M 211






REF 9101 SD (BLACK & SILVER) 29




REF NR-340-MG (GRAPHITE GREY) 9188M 6



REF 9101 SD (BLACK & BLUE) 1






REF 9107 (BLACK & SILVER) 748

REF 9144 LVS (BEIGE) 463










REF 9122 MDS (2TONE GREY) 9





Table 5

52

4.3.4.1.2 Conclusion:

The above analysis shows that the product that is being a pain for the quality the most is

model REF-9144. So we are going to analyze all the data regarding that specific product in

all the next phases.

4.3.4.2 To Determine The Critical Defect: The data used for this analysis is shown in

Table 6 The data that we are using in this analysis is of four months (i.e. from Jan,14 to

Apr,14).

54

4.3.4.2.1 Defects Data Sheet:

Table 6

55

4.3.4.2.2 Conclusion:

The above analysis shows that the defect that is being critically a threat to the process and

effecting the quality is FCP-BEND.

In this stage we are not sure about that until we do Cause and Effect analysis.

4.3.5 Failure Mode Effective Analysis (FMEA):

Failure Mode and Effects Analysis is a method designed to:

Identify and fully understand potential failure modes and their causes, and the effects

of failure on the system or end users, for a given product or process.

Assess the risk associated with the identified failure modes, effects and causes, and

prioritize issues for corrective action.

Identify and carry out corrective actions to address the most serious concerns.

4.3.5.1 Objectives of FMEA:

There are many other objectives for doing FMEAs, such as:

Identify and prevent safety hazards.

Minimize loss of product performance or performance degradation.

Improve test and verification plans (in the case of System or Design FMEAs).

Improve Process Control Plans (in the case of Process FMEAs).

Consider changes to the product design or manufacturing process.

Identify significant product or process characteristics.

Develop Preventive Maintenance plans for in-service machinery and equipment.

Develop online diagnostic techniques.

4.3.5.2 Process/Product Failure Mode and Effects Analysis:

Product

Name: Refrigerator (9122/9144)

Responsible: Foaming Team

Prepared by: Six Sigma Team

FMEA Date (Original): Nov 12, 14

56

Process

Step

Potential

Failure

Mode

Potential

Failure

Effects

SE

V

Potential

Causes

OC

C Current

Controls

DE

T

RP

N

Foaming

FCP bend Gap between Body Liner and FCP.

7

Mold setting of walls. Low

thickness FCP (1mm).

6

Verification of the mold setting that

the body should be

aligned with the side walls.

5 210

FCP deshape

Gap between Body Liner

and FCP. 9

Spot broken.

5

Verification of the mold

setting that the body

should be aligned with the side walls.

3 135

ICP tapered

Gap between Body Liner and ICP.

6

Mold pressing due to limit

switch.

4

Verification of mold setting at the

start of Shift.

4 96

ICP press Gap between Body Liner

and ICP. 7

Wrong bending at

supplier. Mold Pressing.

5

Verification of mold

setting at the start of Shift.

4 140

Z-bottom

deshape

Gap between

Body Liner and FCP. 7

Excess Foam

Weight. Gap between

Mold and Z-bottom

0

Verification

of mold setting. 6 0

4.3.5.3 Conclusion: So we worked on those potential failure modes which has the highest

risk priority rankings as instructed by the external advisor. According to the above study the

defects or failure modes that are potentially ranked as the most severe defects on which we

specifically worked on are:

FCP bend (RPN = 210)

ICP press (RPN = 135)

Further discussion about what are the controls that we have implemented for these failure

modes will be discussed in improve phase.

The tables and standards that we have used in this study so far are given below on the next

page for reference.

57

4.3.5.4 Tables and Standards Used In FMEA:

Table 7

Effect Criteria: Severity of Effect Defined Ranking

Hazardous:

Without

Warning

May endanger operator. Failure mode affects safe vehicle operation and / or involves noncompliance with government regulation. Failure will occur WITHOUT warning.

10

Hazardous:

With

Warning

May endanger operator. Failure mode affects safe vehicle

operation and / or involves noncompliance with government regulation. Failure will occur WITH warning.

9

Very High

Major disruption to production line. 100% of product may have

to be scrapped. Vehicle / item inoperable, loss of primary function. Customer very dissatisfied.

8

High

Minor disruption to production line. Product may have to be

sorted and a portion (less than 100%) scrapped. Vehicle operable, but at a reduced level of performance. Customer dissatisfied.

7

Moderate

Minor disruption to production line. A portion (less than 100%)

may have to be scrapped (no sorting). Vehicle / item operable, but some comfort / convenience item(s) inoperable. Customers

experience discomfort.

6

Low

Minor disruption to production line. 100% of product may have to be reworked. Vehicle / item operable, but some comfort /

convenience item(s) operable at reduced level of performance. Customer experiences some dissatisfaction.

5

Very Low

Minor disruption to production line. The product may have to be sorted and a portion (less than 100%) reworked. Fit / finish /

squeak / rattle item does not conform. Defect noticed by most customers.

4

Minor


of the product may have to be reworked on-line but out-of-station. Fit / finish / squeak / rattle item does not conform. Defect noticed by average customers.

3

Very Minor


of the product may have to be reworked on-line but in-station. Fit / finish / squeak / rattle item does not conform. Defect

noticed by discriminating customers.

2

None No effect. 1

58

Table 8

Probability of Failure Possible Failure Rates Cpk Ranking

Very High: ³ 1 in 2 < 0.33 10

Failure is almost inevitable 1 in 3 ³ 0.33 9

High: Generally associated

with processes similar to previous

1 in 8 ³ 0.51 8

processes that have often failed 1 in 20 ³ 0.67 7

Moderate: Generally associated with processes

similar to

1 in 80 ³ 0.83 6

previous processes which have 1 in 400 ³ 1.00 5

experienced occasional failures,

but not in major proportions 1 in 2,000 ³ 1.17 4

Low: Isolated failures associated with similar

processes

1 in 15,000 ³ 1.33 3

Very Low: Only isolated failures associated with almost

identical processes

1 in 150,000 ³ 1.5 2

Remote: Failure is unlikely. No failures ever associated with almost identical processes

£ 1 in 1,500,000 ³ 1.67 1

Table 9

Detection Criteria: Likelihood the existence of a defect will be

detected by test content before product advances to next

or subsequent process

Ranking

Almost

Impossible

Test content detects < 80 % of failures 10

Very Remote Test content must detect 80 % of failures 9

Remote Test content must detect 82.5 % of failures 8

Very Low Test content must detect 85 % of failures 7

Low Test content must detect 87.5 % of failures 6

Moderate Test content must detect 90 % of failures 5

Moderately High Test content must detect 92.5 % of failures 4

High Test content must detect 95 % of failures 3

Very High Test content must detect 97.5 % of failures 2

Almost Certain Test content must detect 99.5 % of failures 1

59

4.3.6 Cause and Effect Analysis:

For cause and effect analysis we used a tool called Fishbone diagram OR cause and effect

diagram. The fishbone diagram shown below highlights the probable causes of thee defect

that we have identified as potentially most harmful.

MAN

MATERIAL

MACHINE

Nature of the Alloy that is used

Thickness of the plate

Designing parameters

Improper handling

Variation in manually applied pressure

Improper adjustment of body in foaming mold

Improper adjustment of cabinet in the foaming mold

Parameters of spot welding

Foaming parameters

FCP

BEND

Improper Mold Setting

Excess Foam weight

Mold pressing

Spot broken

Gap between Mold and Z-bottom

Improper Alignment of body with side walls of

mold

Improper Mold setting at the start of each shift by worker

60

4.4 IMPROVE PHASE:


The goal of Improve phase is to:

Move on to solution development.

Do a structured improvement that would lead to innovative and elegant solution.



Brain storm solutions that might fix the problem.

Select the practical solution.

Develop maps of the processes based on different solutions.

Select the best solution(s).

Implement the solution(s).

Measure improvements.



FMEA (After Adopting Controls).

Design of Experiment (DOE).

4.4.4 FMEA (Controlled)

Process or Product

Name:FOAMING

Responsible: Foaming Team

Prepared by: Six Sigma team

FMEA Date (Orig) Jan-Apr14 (Rev) Sept-Nov

61

Pro

cess

Ste

p

Pot

enti

al

Fail

ure

Mod

e

Pot

enti

al F

ailu

re

Effe

cts

S E V

Pot

enti

al C

ause

s

O C C

Cur

rent

Con

trol

s

D E T

R P N

Act

ions

Rec

omm

ende

dR

esp.

S E V

O C C

D E T

R P N

FCP

ben

d G

ap b

etw

een

Bod

y

Lin

er a

nd F

CP

.

7

Mol

d se

tting

of

wal

ls.

Low

thic

knes

s FC

P

(1m

m).

6

Ver

ifica

tion

of th

e

mol

d se

tting

that

the

body

sho

uld

be

allig

ned

with

the

side

wal

ls.

521

0

Thi

ckne

ss o

f FC

P

incr

ease

d fr

om 1

mm

to 1

.5m

m.

Alli

gnm

ent o

f th

e

body

and

sid

e w

alls

of th

e m

old

shou

ld

be m

anda

tory

.

Floo

r

Eng

inee

r

74

514

0

FCP

des

hape

d G

ap b

etw

een

Bod

y

Lin

er a

nd F

CP

.

9

Spot

bro

ken.

2

Ver

ifica

tion

of th

e

mol

d se

tting

that

the

body

sho

uld

be

allig

ned

with

the

side

wal

ls.

354

Thi

ckne

ss o

f FC

P

incr

ease

d fr

om 1

mm

to 1

.5m

m.

Alli

gnm

ent o

f th

e

body

and

sid

e w

alls

of th

e m

old

shou

ld

be m

anda

tory

.

Floo

r

Eng

inee

r

92

354

ICP

tape

red

Gap

bet

wee

n B

ody

Lin

er a

nd I

CP

.

6

Mol

d pr

essi

ng d

ue to

limit

switc

h.

4

Ver

ifica

tion

of m

old

setti

ng a

t the

sta

rt

of S

hift

.4

96

Pro

per

Mol

d se

tting

at th

e st

art o

f ea

ch

shift

or

whe

n th

e

mod

el c

hang

es b

y an

expe

rienc

ed w

orke

r.

Floo

r

Eng

inee

r

63

472

ICP

pre

ssG

ap b

etw

een

Bod

y

Lin

er a

nd I

CP

.

7

Wro

ng b

endi

ng a

t

supp

lier.

Mol

d P

ress

ing.

5

Ver

ifica

tion

of m

old

setti

ng a

t the

sta

rt

of S

hift

.

4

140

Ver

ifica

tion

of p

art

draw

ing

at S

QA

.

Pro

per

Mol

d se

tting

at th

e st

art o

f ea

ch

shift

or

whe

n th

e

mod

el c

hang

es b

y an

expe

rienc

ed w

orke

r.

Floo

r

Eng

inee

r

74

411

2

Z-b

otto

m

desh

aped

Gap

bet

wee

n B

ody

Lin

er a

nd F

CP

.

7

Exc

ess

Foam

Wei

ght.

Gap

bet

wee

n M

old

and

Z-b

otto

m0

Ver

ifica

tion

of m

old

setti

ng.

60

Woo

den

jig

inst

alla

tion

betw

een

gaps

of

mol

d.

Ver

ifica

tion

of f

oam

wei

ght a

s pe

r

stan

dard

.

Floo

r

Eng

inee

r

70

60

Foa

min

g

62

4.4.4.1 Conclusion: After the manufacturing team adopted the control measures, significant

improvement in the process can be observed in the above analysis. As the above FMEA

indicates the significant decrement in the risk priority numbers of some potentially harmful

failure modes, therefore we can state that the FMEA performed in the analyze phase has

brought some significant improvements in the process.

4.4.5 Design of Experiment (DOE):

Design of experiments (DOE) is a powerful tool for improving processes as part of a Six

Sigma program. It works best when we know which quality characteristic must be improved,

that there are variables we can change that affect the quality characteristic, we have an agreed

on measuring system for the variables and we can devote resources for manipulating the

variables in an organized way.

4.4.5.1 Experiment Design Guidelines:

The Design of an experiment addresses the questions outlined above by stipulating the following:

The factors to be tested.

The levels of those factors.

The structure and layout of experimental runs, or conditions.

4.4.5.2 Experiment Design Process:

The flow chart below illustrates the experiment design process:

Figure 10 (Design of Experiment)

63

4.4.5.3 Problems Faced By The Six Sigma Team:

The problem faced by the six sigma team in conducting the Design of Experiment is that they have lack of authority towards the implementations of the suggestions to

improve or even temporary implementation of the controls.

4.5 CONTROL PHASE:


The goal of Control phase is to:

Document exactly how the team wants to sustain improvements by passing process

improvement infrastructure on to the employees who work within the process.


Typical steps that should be taken in this phase includes:

Continuously improve the process by using LEAN principles.

Ensure the process is being managed and monitored properly.

Expand the control process throughout the organization.

Apply new knowledge to other process in your organization.



Control Plan.

Control charts.

Documentation.

4.5.4 Control Plan:

Core Team: Six Sigma team Date

2/12/2014

64

Proc

ess

Step

Input

Outpu

t

Proc

ess

Spec

(LSL,

USL,

Targ

et)

Cpk /

Date

(Sam

ple

Size

)

%R&R

or

P/T

Curre

nt

Contr

ol

Metho

d

(from

FMEA

)

Who

W

here

Whe

nRe

actio

n Plan

Foam

ing

Hollo

w

Cabin

et

Solid

Cabin

et

(m

m)

LSL=

0

USL=

2.50.3

430

%Mo

ld Se

tting

QA

engin

eer

Foam

ing

statio

n

At th

e

start o

f

each

shift

Thick

ness

of FC

P inc

rease

d from

1mm

to

1.5mm

. Prop

er ali

gnme

nt of

body

with

the

side w

alls o

f the m

old.

Verifi

catio

n of th

e mold

settin

g at th

e star

t

of ea

ch sh

ift.

Verifi

catio

n of

part d

rawing

at S

QA.

Woo

den j

ig ins

tallat

ion be

twee

n the

gaps

of

mold.

Veri

ficati

on of

foam

weig

ht as

per

stand

ard.

65

4.5.5 Control Charts:

A control chart is graphical tool for monitoring the activity of an ongoing process. We can

use control charts to track process statistics over time and to detect the presence of Special

(Assignable) Causes. It gives great insight into Short-term variations.

4.5.5.1 Basic Principles:

The center line is usually found in accordance with the data in the samples. It is an indication

of the Mean of a process and is usually found by taking the average of the values in the

sample.

A control chart contains:

o A Center Line.

o An Upper Control Limit.

o A Lower Control Limit.

A point that plots within the control limits indicates that the process is in control.

o No action is necessary.

A point that plots outside the control limits is evidence that the process is out of

control.

o Investigation and corrective action are required to find and eliminate special

(assignable) cause(s).

4.5.5.2 Errors In Making Inferences From Control Chart:

4.5.5.2.1 Type-I (alpha) Error:

Results from inferring that the process is out of control when it is actually in control.

Probability of type-I error is denoted by ‘α’

4.5.5.2.2 Type-II (Beta) Error:

Results from inferring that a process is in control when it is really out of control. Probability

of type-II error is denoted by ‘β’

66

4.5.5.3 Analysis Of Pattern In Control Charts: One of the main objective of using control

chart is to determine when a process is out of control so that necessary actions may be taken.

4.5.5.3.1 Western Electric Rule For Out Of Control:

Rule-1: A process is assumed to be out of control if a single point plots outside the

control limits.

Rule-2: A process is assumed to be out of control if two out of three consecutive

points fall outside the 2б warning limits on the same side of the center line.

Rule-3: A process is assumed to be out of control if four out five consecutive points

fall beyond the 1б limit on the same side of the center line.

Rule-4: A process is assumed to be out of control if nine or more consecutive points

fall to one side of the center line.

Rule-5: A process is assumed to be out of control if there is a run of six or more

consecutive points steadily increasing or decreasing.

4.5.5.4 Control Charts for the Current Process:

Referring to the data show in Table 4 we have a sample size of (n = 50), so according to the

rule we can use:

Xbar- R chart.

Xbar- S chart.

4.5.5.4.1 Xbar-R chart:

It monitors the mean and the variation (range) of your process when you have continuous

data in subgroups. According to the rule as the above control chart doesn’t fall in any of the

categories defined in the rules, therefore the process is INCONTROL.

67

4.5.5.4.2 Xbar-S chart:

Monitors the mean and variation (St. Deviation) of your process when you have continuous

data in subgroups. According to the rule as the above control chart doesn’t fall in any of the

categories defined in the rules, therefore the process is INCONTROL.

69

CHAPTER 5

RECOMMENDATIONS

The part that we have been working on to remove the defect from is routed through several

departments/stations within the company. So the recommendations we are going to suggest

here are specific for each of these departments and station.

5.1 SUPPLIER QUALITY CONTROL DEPARTMENT (SQA):

Tolerances given to the vendors should be minimized.

Proper inspection of FCP by well trained and experienced workers.

Sample size of the lot should be increased.

5.2 INVENTORY:

FCP lot should not be increased by a standard amount as calculated by engineering

department.

Proper handling of FCP lot in/out of the inventory department.

5.3 SPOT WELDING DEPARTMENT:

FCP should be placed in an organized way i.e. should not be placed in bulk.

During spot welding jig should be placed properly over the FCP.

Worker should avoid the unnecessary pressing of FCP during spot welding.

Spot welding parameters should be maintained as per given standard and should be

inspected at the start of each shift.

70

Figure 11 (Spot welding Standard Parameters)

71

5.4 PRE FOAMING DEAPARTMENT:

Anti-moisture tube should be placed properly in the body profile without effecting the

FCP.

Proper dispatching of the hollow cabinet from the pre-foaming station to avoid the

foam leakage during foaming process.

Bend status of FCP should be inspected at regular intervals before dispatching the

hollow cabinet towards foaming station.

5.5 FOAMING DEPARTMENT:

Mold setting should be verified at the start of each shift and/or when the model

changed, by a well trained and experienced worker.

Mold setting should also be verified during each shift at regular intervals to control

the defects which arises due to improper mold setting.

Body profile should be well aligned with the side walls of the mold to control the

pressing.

Installation of wooden plank between the gap of mold and cabinet.

Proper verification of foam weight as per standard.

72

Figure 12 (Foaming Mold In Open Condition)

5.6 ENGINEERING DEPARTMENT:

Thickness of FCP should be increased from 1mm to 1.5mm at least in order to avoid

the bending of FCP.

73

REFERENCES

1. Pyzdek, the Six Sigma Handbook, McGraw-Hill, 2003.

2. T.Allen, Introduction to Engineering Statistics and Six Sigma, Springer, 2006. 3. Design for Six Sigma in Product and Service Development, CRC Press, New York,

2012, (05-48).

4. A. Cudney, L. Furterer, Case Study on Design of an Optical Mouse, Design for Six

Sigma in Product and Service Development, CRC Press, New York, 2012, (239-264). 5. A. Cudney, L. Furterer, Case Study on Design of Women’s Centre Service Processes,

Design for Six Sigma in Product and Service Development, CRC Press, New York, 2012, (291-337).

6. http://www.orient.com.pk/about/company-profile/

7. http://www.haier.com/pk/header/201208/t20120816_141283.shtml 8. http://www.singer.com.pk/aboutus.aspx

9. http://pel.com.pk/?page_id=758

10. http://waves.net.pk/about-us/ 11. http://www.dawlance.com.pk/corporate/corporate_value.asp

http://www.orient.com.pk/about/company-profile/

http://www.haier.com/pk/header/201208/t20120816_141283.shtml

http://www.singer.com.pk/aboutus.aspx

http://pel.com.pk/?page_id=758

http://waves.net.pk/about-us/

http://www.dawlance.com.pk/corporate/corporate_value.asp

74

APPENDICES

Month

Jul/13

Aug/1

3Sep

/13Oc

t/13

Nov/1

3De

c/13

Jan/14

Feb/1

4Ma

r/14

Apr/1

4Ma

y/14

Jun/14

YTD

Target

74.00

64.00

73.00

46.00

32.00

27.00

18.00

22.00

20.00

35.00

54.00

111.00

Actua

l133

.3496.

1497.

70102

.2264.

5457.

9548.

0545.

5363.

4383.26

Target

8.00

8.00

11.00

13.00

15.00

22.00

12.00

11.00

10.00

9.00

8.00

7.00

Actua

l14.

979.9

611.

769.2

78.4

810.

6311.

576.5

66.5

010.28

Target

7.36

6.36

6.19

4.14

4.03

3.51

3.98

4.72

5.87

7.01

7.50

10.02

Actua

l8.2

68.3

38.6

07.6

75.5

85.3

44.5

34.5

55.4

26.68

Target

55.00

55.00

55.00

55.00

55.00

55.00

55.00

55.00

55.00

55.00

55.00

55.00

Actua

l95.

2395.

6796.

0680.

46100

.34200

.00152

.86106

.95138

.61104

.87

Target

0.884

0.884

0.901

0.901

0.934

0.951

0.901

0.901

0.901

0.901

0.901

0.901

Actua

l0.7

360.7

690.8

020.9

010.9

010.8

680.8

350.8

020.7

690.82

Machi

ne Pro

cess C

apabili

ty - DP

L-REF

QUALI

TY DA

SHBOA

RD

Qualit

y Cost

(Exte

rnal C

ost ) P

er Unit

- DPL

-

REF

Qualit

y Cost

(Exte

rnal C

ost ) P

er Unit

- WM

SCR R

EF

Qualit

y Cost

(Inter

nal Co

st ) Pe

r Unit

- DPL

-

REF

75

133.34

96.14 97.70 102.22

64.5457.95

48.05 45.53

63.43

74.0064.00

73.00

46.0032.00 27.00

18.00 22.00 20.000.00

20.00

40.00

60.00

80.00

100.00

120.00

140.00

160.00

Jul-13 Aug-13 Sep-13 Oct-13 Nov-13 Dec-13 Jan-14 Feb-14 Mar-14

Quality Cost (External Cost ) Per Unit - DPL-REF

Quality Cost (External Cost ) Per Unit - DPL-REF Target

8.26 8.33 8.607.67

5.58 5.344.53 4.55

5.427.36

6.36 6.19

4.14 4.033.51

3.984.72

5.87

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

10.00


SCR DPL-REF

SCR REF Target

76

95.23 95.67 96.0680.46

100.34

200.00

152.86

106.95

138.61

55.00 55.00 55.00 55.00 55.00 55.00 55.00 55.00 55.000.00

50.00

100.00

150.00

200.00

250.00


Quality Cost (Internal Cost ) Per Unit - DPL-REF

Quality Cost (Internal Cost ) Per Unit - DPL-REF Target

0.7360.769

0.802

0.901 0.9010.868

0.8350.802

0.769

0.884 0.884 0.901 0.9010.934 0.951

0.901 0.901 0.901

0.55

0.60

0.65

0.70

0.75

0.80

0.85

0.90

0.95

1.00


Machine Process Capability - DPL-REF

Machine Process Capability - DPL-REF Target

77

STATION_NAME BODY FOAMING

Count of DEFECT_DESC MONTH

DEFECT_FAMILY SKU_ITEM_NAME DEFECT_DESC Jan/14 Feb/14 Mar/14 Apr/14 Grand Total

DENTED 1910 1867 2165 1684 7626

NOTCHING 134 252 294 303 983

FOAM LEAK 128 251 286 297 962

BODY LINER 111 110 256 374 851

FREEZER FRAME 132 203 96 324 755

SCRATCH 128 121 96 112 457

DRAIN 40 126 67 84 317

SHORT FOAM 84 56 18 29 187

PAINT 56 24 47 48 175

PP SHEET 2 18 74 78 172

EVAPORATOR 8 31 44 26 109

FCP 14 35 12 30 91

ICP 19 26 13 13 71

WAVES 9 7 21 29 66

DESHAPE 5 14 20 22 61

FREEZER SIDE PLATE 19 8 14 14 55

PRESS 9 8 15 32

BODY PROFILE 1 10 8 7 26

Z-BOTTOM 1 12 2 5 20

CLEANING 6 5 2 1 14

SOFT FOAM 1 1 11 13

CHIPPING 6 1 4 1 12

RUST 1 1 1 3

Grand Total 2824 3178 3549 3507 13058

78

Jan-14

Row Labels Count of SKU_ITEM_NAME













REF 9106 SD (BLACK AND BLUE) 2

Grand Total 7420

Feb-14

Row Labe ls Count of SKU_IT EM_NAME










REF NR-340-MG (PEACH BROWN) 9188M 211










REF NR-340-MG (GRAPHITE GREY) 9188M 6



REF 9101 SD (BLACK & BLUE) 1

Grand T ota l 12032

79

Mar-14

Row Labels Count of SKU_ITEM_NAME






REF 9107 (BLACK & SILVER) 748

REF 9144 LVS (BEIGE) 463










REF 9122 MDS (2TONE GREY) 9





Grand Total 11624

implementation of six sigma

Documents