Six Sigma Tools

3rd Batch of 3 Days Refresher Course designed for SIX SIGMA BB/ GB Holders

(Application of Shainin DOE tools)

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Agenda Day-1

•Need of Six Sigma & D.O.E.•Pre- knowledge Test•DMAIC Process•D.O.E. Tools & Their Applications.

•Paired comparison•Product / Process Search•Concentration Chart.

Six Sigma- D.O.E.

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Agenda Day-2

•D.O.E. Tools & Their Application (Contd..)• Recap / Exercise on the previous days tools.• Component Search.• Modified Component Search.• Multi Vari Analysis

Six Sigma- D.O.E.

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Agenda Day-3

• Recap / Exercise on the previous days tools.•B Vs C Analysis•Control Phase.• Q & A Session to clear the doubts.•Post Knowledge Test• Presentation by each group / member on the projects selected ( templates given only need to be used)• Date & Time for the next meeting in the month of Jan ’09

Six Sigma- D.O.E.

Slide: 5

Brief Introduction of ACT &

SIX SIGMA CLUB

ACT- ACMA Centre For Technology

Objective of ACT

To make our members globally competitive in order to meet the increasing demand of QCD

from the customers

7

Present ACT Activities1.ACT Foundation Cluster

2.ACT- UNIDO Cluster

3.Advance Cluster on Lean.

4.ACMA Awards

5.AOTS program in Japan

6.AOTS program in India

7.WP.29- World Forum for Harmonization of Vehicle Regulations

8

Present ACT Activities8.NATRIP-National Automotive Testing and R&D Infrastructure Project

9.TIFAC – Technology Information, Forecasting & Assessment Council

10.CMVR- Centre Motor Vehicle Rules.

11. AIS-Automotive Industry Standards

12. BIS- Bureau of Indian Standards

13. National QC Convention.

14. Plant Visits & Technical Conferences.

9

Launch of ACT publication ”ACTnow”- ACT magazine is released on 4 monthly basis, covers the major activities done by ACT during that period while focusing one activity of ACT in detail. Also the cluster journey of one company, who have undergone ACT Cluster, is published in every issue. Five issues have already been released by now.

10April ’07 IssueAugust ’07 Issue

ACT Publication

August’08 Issue

December’07 IssueApril’08 Issue

SIX SIGMABack Ground:• First Batch of Black Belt Six Sigma Certification program was launched in Northern Region on 11th

Nov’2003.

•Program was customized & developed to suit ACMA member companies with the help of outside faculty Mr. Ramnarayan.

•Overwhelming response received from the members.

•Program was extended across all the regions.

SIX SIGMA

Status as on Mar’08:

SIX SIGMA

Results:

• In spite of the best efforts implementation was poor.

•At the same time the demand of High Quality & Low Cost is increasing day by day.

SIX SIGMA

Challenges ahead:

•Keep this momentum alive.•Expand the scope and understanding with more companies.•Exchange ideas among Six Sigma Black Belt & Green Belt Holders.

•Enhance implementation of the knowledge .•To promote Six Sigma Culture within the organisation for sustenance.•To address customers’ demand of ZERO Defect Supplies.

SIX SIGMA CLUB

Creation & Development of

Six Sigma Club was an option to address all these Challenges

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Six Sigma Club website was launch on 6th September 07 in ACMA’s AGM. This website would provide following features to Club members:

(1) Discussion Forum.

(2) Latest circulars regarding various training programmes.

(3) Case Studies / Technical Documents.

Website Address: www.acmainfo.com/six-sigma

SIX SIGMA CLUB

Execution Plan:

Organization Structure:

•Formation of Six Sigma Club Executive committee, out of the members who had undergone Six Sigma certification course & obtained Black Belt / Green Belt status.

•Appointment of co-coordinator from ACMA secretariat.

SIX SIGMA CLUB

Eligibility Criteria:

•Eligible for all ACMA member companies.•Member has to be Six Sigma Black Belt or Green Belt Holder.•Membership would be given at the company level only . However company can nominate any number of its employees.•Member holding any position in the Executive Committee necessarily have to be Black Belt or Green Belt holder.

SIX SIGMA CLUBExecution Plan:

Proposed Activities of Six Sigma Club:

•Launch of Six Sigma Club Web Site.•To hold Seminars & Conventions.•To share various Six Sigma Projects Completed.•To update the status of activities done by individual companies on SIX SIGMA CLUB Website.•Sharing information related to Six Sigma across the industries.•Refresher course for BB/GB holders

SIX SIGMA CLUB

Execution Plan:

Communication Management:

•Through an active SIX SIGMA CLUB Website , administratively controlled by ACT Office.

•Telephonic Conversations.

•Conferences , Visits & Seminars.

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D.O.E……Shainin Tools of Design of Experiments

Six Sigma- D.O.E.

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Introduction of Six Sigma

Six Sigma was first time developed & introduced by Sir Bill Smith in Motorola in 1987.

Six Sigma- D.O.E.

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Introduction of Six Sigma

•Sigma represents variation in the process wrt mean (average line).•Every process will have certain variation which is natural because no two things are identical.

Six Sigma- D.O.E.

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Six Sigma- D.O.E.

Process Variations

Input Material Variations

Poor Process Design

Poor Product Design (Tolerancing)

MachineTooling Parameter

Variation MethodVariation

Processing Material

Environment

Sources of Variations

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Six Sigma- D.O.E. Lower Spec limit Upper Spec limitNominal Target

Process Mean 6 Sigma represents Part to part variation

•6 Sigma= Tolerance•% Defectives= 0.27 %

•3 Sigma LevelDefects

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Six Sigma- D.O.E. Lower Spec limit Upper Spec limitNominal Target

Process Mean 6 Sigma

represents Part to part variation

•6 Sigma= 50 %Tolerance•% Defectives= 3 ppb•6 Sigma Level Objective :

Zero Defects Reduce variations

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Six Sigma ?

•Variation is nothing but its Part to Part Variation (PPV).•Control of variation in the process (PPV) less than 50 % of the Tolerance is called Six Sigma.

Six Sigma- D.O.E.

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Six Sigma ?

• 6 Sigma = PPV is less than 50 % of the Tolerance.•Rejection Level=3ppb.

Six Sigma- D.O.E.

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Objective of Six Sigma

• To Achieve Zero Defects by Reducing Process Variations.

Six Sigma- D.O.E.

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Why DOE Tools?

Six Sigma- D.O.E.

•Most Scientific way to find out the root cause of the problem•DOE tools identify the Root Cause of the Problem based on the data not by assumptions.

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DOE Tools application by,

Six Sigma- D.O.E.

•Taguchi Methods•Shainin Methods

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Introduction of Shainin DOE Tools

Six Sigma- D.O.E.

DOE (Design of Experiments) Tools, developed by Shainin based on statistics, help in achieving the objective of Six Sigma Level in each process of the organization .

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Why Shainin DOE ?

Six Sigma- D.O.E.

•Simple & Clear- No complexity in the process of data collection & its analysis.•Data collection can be done on-line without stopping or disturbing the regular production.•No complex mathematics, statistics used while analyzing the data & find out the root cause.•Conclusion are drawn based on the data without having any ambiguity.

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Shainin DOE Tools- 8 Problem Solving Tools

Six Sigma- D.O.E.

1. Paired Comparison.2. Product / Process Search.3. Concentration Chart.4. Component Search.5. Modified Component Search.6. Multi-Vari Analysis.7. B Vs C Analysis.8. Variable Search.9. Variable Search.

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Shainin DOE Approach

Six Sigma- D.O.E.

DMAIC

DefinePhase-1

Measure &

Analyze

Phase-2

Phase-3Improve

Phase-4Control

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DMAICSix Sigma- D.O.E.

Phase –1-D- Define- After selection of the project for Six Sigma based on Pareto Analysis, CTC,CTQ,Define the Problem Clearly & calculate COPQ( Cost of Poor Quality).Phase-2-M&A-Measure & Analysis the data using appropriate DOE Tools to pin point the Sources of Variation (SSV) & identifying Root Cause .Phase-3-I-Improve –Actions are taken to eliminate the source of variation for the root cause identified.Phase-4-C-Control-Process controls methods are set to ensure that the counter measure taken in phase –3 stays permanently.

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DMAIC & ToolsSix Sigma- D.O.E.

Phase Tools

1-Define1. Pareto Analysis.2. Process FMEA.

2-Measure & Analyze

1. 8 DOE TOOLS

3-Improve 1. B vs C

4-Control1. Variation analysis.2. Control Charts.3. Pre- Control Charts.

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SHAININ DOE TOOLS FOR PROBLEM SOLVING

Six Sigma- D.O.E.

Phase-1: Define

• Step-1: Define the Quality Problem clearly.•Step-2: Write down Part Name, Part No., Specifications, Tolerances & Instrument used.•Step-3: Mention least count of the instruments used( should be 1/10 th of the tolerance allowed)•Step-4: Mention the nature of problem.... Attribute or Variable.•Step-5: Calculate & mention COPQ.•Step-6: Write down the Sources of Variations (SSVs)for the problem.

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Six Sigma- D.O.E.

Y = f(x)Where ‘Y’ = Response ( Actual Problem)

‘X’ = Sources of Variations ( Probable causes of the Problem)

Note : Only those SSVs are to be considered wherein variation is possible & should be able to

measure ( Quantify)

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Six Sigma- D.O.E.

Phase-2: Measure & Analysis• Step-1: Selection of DOE Tools for all SSVs one by one based on the selection criterion.•Step-2: Data Collection and Applying the respective DOE Tool . •Step-3: Analysis the data & finding out the Root Cause of the problem.

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Six Sigma- D.O.E.

DOE TOOL–1: Paired ComparisonApplication:

Can be used only when the SSVs are measurable on both Good & Bad Products.( Good & Bad parts are selected based on the response / effect of the problem defined)

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Six Sigma- D.O.E.

DOE TOOL–1: Paired Comparison

Example :

Y= Poor draw ability X’s = 1) % of C in material(Erickson cup value- Crack ) 2) Thickness of coil

3) Hardness of coil4) Annealing Time5) Annealing Temp

We can use Paired comparison tools for 1 & 3 & not for 2,4 & 5 .

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Six Sigma- D.O.E.

DOE TOOL–1: Paired Comparison ( contd..)Step-1: Select 8 BOB( Best of Best) & 8 WOW ( Worst of Worst) Parts based on Response (Y).Min. should be 6.Step-2: Record all the values of ‘x’ in a table for a particular SSVs and write the corresponding response ‘Y’ of that value. Take one by one.Step-3: If SSV is an attribute ,quantify the observations on 1~ 5 Scale.Step-4:Arrange the data in the ascending order.

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Six Sigma- D.O.E.DOE TOOL–1: Paired ComparisonExample:

XY1.22BOB1.23BOB1.25BOB1.39WOW1.39 WOW1.40 WOW1.40BOB1.41 BOB1.41 WOW1.45WOW1.45WOW1.47 BOB

XY1.22BOB1.23BOB1.25BOB1.39WOW1.39 WOW1.40 WOW1.40BOB1.41 BOB1.41 WOW1.45WOW1.45WOW1.47 BOB

Step d – If the values above and below the

transition line are common more than 2

than. Treat entire block as one data and draw

transition line.

Step c- If 2 values above and below the transition line are common reduce

0.5 from the count, upper and lowercase both

Step b – From top , Draw line where transition

takes place. - From bottom also do

the sameStep a-Arrange values in

ascending order

XY1.22BOB1.23BOB1.25BOB1.39WOW1.39 WOW1.40 BOB1.40BOB1.41 BOB1.42 WOW1.45WOW1.45WOW1.47WOW


XY1.22BOB1.23BOB1.25BOB1.25 WOW1.39 WOW1.40 BOB1.40BOB1.41 BOB1.41 WOW1.45WOW1.45WOW1.47WOW

XY1.22BOB1.23BOB1.25BOB1.25 WOW1.39 WOW1.40 BOB1.40BOB1.41 BOB1.41 WOW1.45WOW1.45WOW1.47WOW



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Six Sigma- D.O.E.

DOE TOOL–1: Paired Comparison ( contd..)Step-5:Count the numbers as per following guidelines:a) If both Topmost & Bottommost values of ‘x’ belong to

same category of response ‘y’, ‘GOOD’ or ‘BAD’ , the count is ZERO.

b) If condition ‘a’ do not fulfill , see for the transition line from Top & Bottom both independently where ‘Good’ Changing into ‘Bad’ or Bad is changing into Good. Draw the line at transition. Count the Number above & below the transition line & add. This is the total count for that SSV.

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Six Sigma- D.O.E.


c)Check at the transition line,if the 2 values are common,deduct 0.5 from the total count. Applicable for both upper & lower block.d) Check at the transition line ,if the values above & below are common > 2 , make a block and consider the full block as a transition line.Count above the line for upper block & below the line for lower block.

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Six Sigma- D.O.E.

DOE TOOL–1: Paired Comparison ( contd..)

Step-6:Conclusion•If the Total counts are >= 6 , Proposed SSV is a Cause of the problem .If count is < 6 ,its not a cause & to be ignored.

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Six Sigma- D.O.E.

DOE TOOL–1: Paired Comparison ( contd..)

Count & Confidence Level:Count CL %

6

7

10

13

90%

95%

99%

99.9%

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Six Sigma- D.O.E.

Phase-3: Improve

DOE TOOL–1: Paired Comparison ( contd.)

Step-7:•Deciding the Spec for ‘SSV’ having count>6 from the data analyzed.

For all the causes with Count >=6, fix the specification based on the “GOOD” band

Fine tune the specification by adding or subtracting the existing tolerance depending on where the GOOD band is located

For geometrical parameters, Do not do fine tuning, Fix only USL based on the data, since the LSL is always zero

Calculate the variation as the maximum – minimum of all the 12 or 16 data

If the Variation is <=75% of the New tolerance, then the Confirmed cause is a “ROOT CAUSE”If the Variation is >75% of the New tolerance, then the Confirmed cause is only a “CAUSE” and this should be taken as Y and drilled down further

Six Sigma- D.O.E.

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Six Sigma- D.O.E.

Phase-3: Improve


Step-8:•Is that the new specification is controllable ? If answer is ‘Yes’ , make the improvement plan & implement.

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Six Sigma- D.O.E.

Phase-3: Improve


Step-9:

• If answer is ‘ No’. Investigate the reasons ( X–SSV ) for such variation ( Response –Y ) & find out the root cause.

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Six Sigma- D.O.E.


Example :

Refer Case Study-1

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Six Sigma- D.O.E.

DOE TOOL–2: Product / Process SearchApplication:

SSVs related to the Process Parameters or Input Material which can not be measured on both Good & Bad parts, ‘Product / Process Search’DOE Tool Used. Examples: Temperature, Pressure ,Pouring time, Input material wherein dimensions get changed during processing like: Drill dia in the case of Thread Loose or Tight Problem.

( Good & Bad parts are selected based on the response / effectof the problem defined )

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Six Sigma- D.O.E.

Phase-2: Measure & AnalysisDOE TOOL–2: Product / Process Search ( contd..)

Step-1: Collect the values of SSV ‘x’ from the previous process / product & measure the Response ‘Y’ till we get min. 8 BOB & 8 WOW. OrIf collection of the data is not possible from the running process ( Inspection time is higher than the Production Cycle Time), select the lot size based on the historical rejection wherein part to part variation should get captured min 80% of the Tolerances specified.Step-2: Record all the values of ‘x’ in a table for a particular SSVs and write the corresponding Response ‘Y’ of that value.

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Six Sigma- D.O.E.

Phase-2: Measure & Analysis

DOE TOOL–2: Product / Process Search ( contd..)

Step-3: Find out the Counts & decide the contribution of each SSV one by one in the problems defined.Step - ‘4 & 5 ‘:are common to Paired Comparison as mentioned in the Previous slides .

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Six Sigma- D.O.E.


Step-6:Conclusion•If the Total counts are >= 6 , Proposed SSV is a Cause of the problem .If count is < 6 ,its not a cause.

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Six Sigma- D.O.E.

Phase-3: ImproveDOE TOOL–2: Product / Process Search( contd.)

Step-7:•Deciding the Spec for ‘SSV’ having count>6 from the data analyzed.

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Six Sigma- D.O.E.

Phase-3: ImproveDOE TOOL–2: Product / Process Search ( Contd..)

Step-8:•Investigation for such variation & make Improvement plan for the above Spec.

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Six Sigma- D.O.E.


Step-9•If the Input material found to be the root cause, we have to continue further analysis applying paired comparison or product Process Search.Step-10•If the root cause established is the Process parameter variation, we need to introduce controls in the machine

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Six Sigma- D.O.E.

Phase-2: Measure & AnalysisDOE TOOL–2: Product / Process Search( contd.)

Step-11•If the Root cause established is neither related to Input Material nor to Process parameters Variation, We have to apply Variable Search for redesigning the Process parameters.

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Six Sigma- D.O.E.

DOE TOOL–2: Product / Process searchExample :

Y= Crack during Draw operation X’s = 1) Annealing Time2) Annealing Temp3) Hardness variation

We can use Product / Process search tool for 1,2& Paired comparison for 3 .

Y = Internal Thread in the bush is Loose X’s = 1) I.D. of the Bush2) Spindle Vibration

W We can use Product / Process search tool for 1 & 2 & not the Paired C Comparison Tool.

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Six Sigma- D.O.E.

DOE TOOL–2: Product / Process searchExample :

Refer Case study-2

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Six Sigma- D.O.E.

Phase-2: Measure & AnalysisDOE TOOL–3: Concentration Chart

Application:Concentration Chart is mostly used for the attribute type of defects to identify It’s intensity at various location / sector.

Is used when defect can generate at multiple streams from the process and streams are too high to apply Multi-Vari Analysis.

Example: Dents, Scratches, Burrs, Paint peel off, Dust, Porosity & Blow Holes in casting.

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Data Collection Analysis ConclusionCollect 30 bad parts Calculate for each zone, the Weighted

sum of the severityIf in any zone the defect severity % is

>=50%, then the defect is concentrated in that zone

Scale the severity of defect on a scale of 1-3. 1 – Less severity 2- Medium

severity 3 – High severity

Calculate the % with respect to the total in each zone

If in all the zones the defect severity is <50%, then the defect is coming

randomly

Divide the part into different zones depending on the geometry

Count on every part, the number of defects generated in each zone

Note down the severity in each zone

Refer Case Study-2

Six Sigma- D.O.E.

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Six Sigma- D.O.E.

Phase-2: Measure & AnalysesDOE TOOL–4: Component Search ( contd.)

DOE TOOL-5: Modified Component SeDOE TOOL- 6: Multi -Vari Analysis

Refer Flow Diagram

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Refer Case study for CS & MVA Tool

Six Sigma- D.O.E.

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B Vs C

Six Sigma- D.O.E.

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M&A and Improvement Phase DOE 7 – B Vs C

Application:• Is used to validate the root cause of the problem identified

using other DOE tools. (DOE Tool 1-6)

• If the cause is validated, then we can calculate how much the improvement has taken place

• Tool is applied only when B & C condition can be created alternately.

• Response is monitored in terms of Big Y

Key Skill of BB : “ Selection of Correct Tool”

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Data Collection Analysis ConclusionIf the tool used for finding out the cause or root cause is Paired comparison or Product/Process search and the total count is full count (16 or

12), then the sample size is 3B and 3C

For 3B and 3C, check whether is there any overlap in the data or not. If there is no overlap,

then the cause is validated

If there is Overlap, then increase the sample size by another 3 and validate as per 6B,6C

For 3B, 3C, if there is no overlap, then the root cause is validated

For 3B, 3C, if there is a overlap, then increase the sample size by 3

In all other situations, the sample size is 6B, 6C For 6B, 6C, find out the count using the same rules as “Paired comparison”

For 6B,6C if the total count is >=6, then the cause is validated

If the response is variable, produce 6 or 3 pieces in B condition and 6 or 3 Pieces in C

condition

For 6B,6C, if the total count is <6, then the cause is not validated and we have to go

back to M&A phase

If the response is attribute, produce 6 or 3 batches in B condition and 6 or 3 batches in C

condition

Quantifying Improvement Quantifying improvement

If the response is variable, measure the actual value of the response as the data for analysis

Quantify improvement only when the cause as per the above rule is validated

If (Xb – Xc) is >= K * Sigma (b), then the amount of improvement can be declared at 95% CL. If it is less, then get the K value at

90% CL and do the same check

If the response is attribute, rejection % in each batch will be taken as the data for analysis

When calculating average, round off the decimal place to one decimal more than the data

If (Xb-Xc) is < K* Sigma(b) even at 90% CL, increase the sample size in multiples of

3

If the validation is done using batches, decide the batch quantity to get at-least one bad

product. Eg: if the historic rejection is 1%, then the batch quantity will be taken as 100 pcs

When calculating Sigma (b), round off the decimal to one decimal more than the data

Maximum boundary for the sample size is 12B, 12C.

In 12B, 12C, if the amount of improvement cannot be declared, then go back to M&A

phase

Always collect data by alternating between the B and C condition

B vs C

VALIDATION OF ROOT CAUSE

RESPONSE : VARIATION IN DIM 91.75 FOUNDS AT HIGHER ( 92.2 – 92.9 )

ASSUMPTOIN : THE RESPONSE WITH B CONDITION MAY OVERLAP WITH RESPONSE WITH C CONDITION

ROOT CAUSE: FOR PIPE WELDING OPERATION , FIXTURE IS REQUIRED

1

B vs C DATA COLLECTION

HERE T.C. = 10

SO ROOT CAUSE IS VALIDATED

HERE WE HAVE TAKEN 6 B PARTS & 6 C PARTSB = DIM 91.75 WITH NEWLY PROVIDED FIXTUREC = DIM 91.75 WITOUT FIXTURE / BY MANUAL OPERATION

92.2892.6491.8192.6191.6991.6091.7492.7292.3291.6891.9291.66C CATB CAT

DIM 91.75ASC ORDER

91. 60 G

91. 61 G

91. 64 G

91. 66 G

91. 68 G

91. 69 B

91. 72 G

91. 74 B

91. 81 B

91. 92 B

92. 28 B

92. 32 B

2

B vs C DATA ANALYSIS & CONCLUSION

X bar-b = 91.651

X bar-c = 91.960

Diff X bar = 0.309

K for 95 % CL = 2.96

Sigma-b = 0.041

Sigma-b * k = 0.121

AS Diff X bar > Sigma-b * k SO ROOT CAUSE IS VALIDATED WITH 95 % C.L.

Refer Case study

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Types of Process Variations

•Part to Part Variation. .( Range Variation- R )

•Time to Time Variation(Mean Variation- X Bar)•Stream To Stream Variation.( Fixture or Tool to

Tool Variation)

Six Sigma- D.O.E.SHAININ DOE TOOLS FOR PROBLEM SOLVINGPhase-4: Control

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Reason for Part to Part Variation(Range)

• Machine• Input Material• Measurements• Operator

Six Sigma- D.O.E.

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Reason for Time to Time Variation ( Mean Shift)

•Variation between one time block to another time block like:• Shift Change, Tool Change, Material Change, Operator Change etc….• Tool Wear

Six Sigma- D.O.E.

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Reason for Stream to Stream Variation

• Product Stream ( Diameter at various locations etc…)

• Process Stream ( Multiple cavities, spindles , fixtures etc…)

Six Sigma- D.O.E.

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Steps before calculating Process Capability or implementing Control Charts.

Phase-IV: Control

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Based on the above analysis, can you conclude that the histogram is Normal

0.0004Range = Maximum Value - Minimum Value 0.004

Construction of HistogramNumber of Groups = Sqrt (Number of data points) 11

Class Interval (C.I) = Range/Number of groups

Yes/NoAre there two Modes (Two groups having maximum frequency) and both the groups are distinctly seperated Yes/No

Class Inverval (C.I) after rounding off to the nearest multiple of the Least count

Draw the Histogram here

Yes/NoIs there a gradual decreasing trend in frequency on both sides of the group having the maximum frequency

Does the Overall Average lie in the group having maximum frequency or in the adjacent groups

Yes/No

Note: If the Histogram is non-normal, do not proceed further for analysis

-3σ -2σ -1σ μ +1σ +2σ +3σ

Phase-IV: Control

80

No If yes write causes (if possible)

NA

0.001

0.006

Sigma = R-bar/d2

6 * Sigma

Are there 7 consequtive points increasing, decreasing and one side of the Mean range

If the Process is not stable even after Homogenization, STOP HERE. Do not proceed further in the analysis. Identify the sources of variations for the instability and correct it

Sigma Calculation

Sample d22 1.128 3 1.6934 2.0595 2.3266 2.534

Phase-IV: Control

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Quality-Module

1. Continue to use Control chart 2. Modify the Control Limits

1. Continue to use Control chart

Actions decided based on Six Sigma Analysis6 Sigma < Tolerance

6 Sigma = Tolerance6 Sigma > Tolerance

6 Sigma > Tolerance

2. Question the basis of Tolerancing 2. Change the process

6 Sigma = Tolerance

3. Use DOE tools to reduce 6 Sigma

1. Use DOE tools

3. Do 100% inspection 3. T ighten the Tolerance 4. Discontinue 100% inspection 4. Do 100% inspection

6 Sigma < ToleranceSix Sigma Analysis

Phase-IV: Control

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Control Charts

Six Sigma- D.O.E.

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Types of Control ChartsControl Charts

Variables Attributes

• p Chart• C Chart

• Pre control Charts•X bar- R chart

Six Sigma- D.O.E.

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VARIABLE CONTROL CHARTSVARIABLE CONTROL CHARTS

Six Sigma- D.O.E.

85

0900 0930 1000 1030 1100 1130 1200 1230 1300

0900 Hrs 0930 Hrs 1000 Hrs 1030 Hrs 1100 Hrs 1130 Hrs 1200 Hrs 1230 Hrs 1300 HrsX-bar 73.577 74.585 74.717 73.233 75.408 75.576 75.414 74.274 74.552

Range 5.232 7.379 4.746 6.834 5.964 8.581 7.508 7.068 8.408

Time

Control Chart for Washer Thickness (mm)

70.00071.00072.00073.00074.00075.00076.00077.00078.00079.00080.000

Mea

n)

00.00002.00004.00006.00008.00010.00012.00014.00016.000

Ran

gePhase-IV: Control

86

A Process is in Control if• No sample points are outside limits• Most points near process average• About equal # points above & below centerline• Points appear randomly distributed

Interpretation of Control Charts

Phase-IV: Control

87

The following is set of the rules:2 out of 3 consecutive values of X on the same side of the CL (Centre line) and more than 2 SD (Standard deviations) from the CL.4 out of 5 consecutive values of X on the same side of the CL and more than 1 SD from CL.8 consecutive points are on the same side of the CL.7 or more consecutive values in a consistently rising or falling pattern.a recurring cyclic pattern.abnormal clustering close to the CL.clustering of values close to both Control limits (suggests is following two distributions instead of one).

Interpretation of Control Charts (Contd.)Phase-IV: Control

88

Control Chart Patterns

CL

LCL

UCL

Sample statistics consistently decreasing.

CL

LCL

UCL

Sample statistics consistently increasing.

X-bar Chart Causes R Chart CausesDeterioration of MachineTired OperatorTool Wear

Improvement / Deterioration of Operator SkillTired OperatorChange in Incoming Material Quality

TRENDSPhase-IV: Control

89

CL

LCL

UCLPROCESS IN-CONTROL

Process operating ONLY under the influence of Chance (Inherent) Variation.

Control Chart Patterns

Phase-IV: Control

90

Pre Control ChartApplication : Used when the actual Part to Part variation ( R bar) is <= 50 % of the Tolerance.

Six Sigma- D.O.E.

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25 % ofTolerance

Yellow Zone

Yellow Zone

Green Zone

Red Zone

Red Zone

25 % ofTolerance50 % ofTolerance

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