To see a block again, you can hit the To see a block again, you can hit the PP (for (for PPreviousrevious) key.) key.(There is no need to do so now).(There is no need to do so now).

WelcomeWelcome –– Course InstructionsCourse Instructions Whenever you see this Whenever you see this iinfo button, you can (and nfo button, you can (and should) click on it to see more information on the should) click on it to see more information on the relative topic. relative topic. Try it nowTry it now – there is a lot of good – there is a lot of good additional info there! additional info there!

When you are finished When you are finished reading its information reading its information window, just click any- window, just click any- where in this where in this iinfo window nfo window to close it. Try it now.to close it. Try it now.

At any time, you can hit ‘At any time, you can hit ‘ ’ on your keyboard to see the ’ on your keyboard to see the NNextext slide or next text block (paragraph) on the page. slide or next text block (paragraph) on the page. Most of the time, the text blocks will appear on their own. Most of the time, the text blocks will appear on their own.

©© Qi Qi22, 2005, 2005

NN

In the table of contents, which starts on the following In the table of contents, which starts on the following screen, you can just click on any lesson to link directly screen, you can just click on any lesson to link directly to it. There are also optional end-of-lesson quizzes.to it. There are also optional end-of-lesson quizzes.

Try hitting the Try hitting the NN key now. key now.

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www.qualityi2.com

Also, you will want to download Minitab (Also, you will want to download Minitab (www.minitab.com) when you are ready to use it in this and in the other 6S modules. The demo is fully functional and is good for 30 days.

SOME THINGS TO KNOW ABOUT CUSTOMERS SOME THINGS TO KNOW ABOUT CUSTOMERS

Problems Decrease Customer LoyaltyProblems Decrease Customer Loyalty

Studies suggest that a company loses approximately one customer Studies suggest that a company loses approximately one customer purchase for every five customers encountering problems. purchase for every five customers encountering problems.

Therefore, for every five problems it prevents or fixes, the company Therefore, for every five problems it prevents or fixes, the company will retain the sales of the one customer who was saved. will retain the sales of the one customer who was saved.

Most Customers Do Not Complain Most Customers Do Not Complain

On the average, 25% of customers having problems do not complain. On the average, 25% of customers having problems do not complain.

So, customer complaints, questions and requests for info and So, customer complaints, questions and requests for info and assistance must be actively encouraged. assistance must be actively encouraged.

Many of the customers who do complain, do so to the wrong people.Many of the customers who do complain, do so to the wrong people. The formal service system usually receives only 10 – 60% (average The formal service system usually receives only 10 – 60% (average 35%) of the total complaints offered. 35%) of the total complaints offered.

Contd.Contd.So, for every complaint received through the complaint system, there are So, for every complaint received through the complaint system, there are about 12 unhappy customers and 2 or more lost sales.about 12 unhappy customers and 2 or more lost sales.

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WHO IS THE BETTER SHOOTER? WHO IS THE BETTER SHOOTER?

JoeJoe

On average,On average, dead ondead on

MaxMax

On average,On average,way offway off

Who is more likely to be consistently on target over the long haul? Who is more likely to be consistently on target over the long haul?

NextNext

WHO IS THE BETTER SHOOTER? WHO IS THE BETTER SHOOTER?

JoeJoe

On average,On average, dead ondead on

MaxMax

On average,On average,way offway off

How do you adjust Joe’s How do you adjust Joe’s shooting process? What shooting process? What happens if you try? The whole happens if you try? The whole pattern will shift – farther from pattern will shift – farther from the target.the target.

You can adjust Max’s process rather You can adjust Max’s process rather easily. All you have to do is adjust easily. All you have to do is adjust the site, which is like shifting the the site, which is like shifting the mean in a process.mean in a process.

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WHO IS THE BETTER SHOOTER? WHO IS THE BETTER SHOOTER?

JoeJoe

On average,On average, dead ondead on

If Joe’s first shot were high, what would be tempted to do with his site?If Joe’s first shot were high, what would be tempted to do with his site?Adjust it down, right? (See next slide)Adjust it down, right? (See next slide)

WHO IS THE BETTER SHOOTER? WHO IS THE BETTER SHOOTER?

JoeJoe

On average,On average, dead ondead on

But if his next shot were below the target do to his natural shooting But if his next shot were below the target do to his natural shooting variation, look at what would happen.variation, look at what would happen.

See next slide.See next slide.

WHO IS THE BETTER SHOOTER? WHO IS THE BETTER SHOOTER?

JoeJoe

On average,On average, dead ondead on

The amount of process adjustment actually moves the The amount of process adjustment actually moves the second shot an equal amount further from where it would second shot an equal amount further from where it would have been without the adjustment. This is called have been without the adjustment. This is called tampering. tampering.

WHO IS THE BETTER BOWLER? WHO IS THE BETTER BOWLER?

BowlingBowling ScoresScores

X X

Pat (X= 150) JaneJane

(X= 140) (X= 140)

15 consecutive15 consecutive game scores game scores

15 consecutive15 consecutive game scores game scores

Time Time

When there is a lack of consistency between measured responses, thereWhen there is a lack of consistency between measured responses, thereis less certainty (i.e., more risk) about what you can expect over time. is less certainty (i.e., more risk) about what you can expect over time.

Although Jane’s average score (x-bar) of 140 is lower than Pat’s, she is atAlthough Jane’s average score (x-bar) of 140 is lower than Pat’s, she is atleast more consistent.least more consistent.

If X is the bowling score, then X (“If X is the bowling score, then X (“x-barx-bar”) is the average score.”) is the average score.

CustomerCustomer RequirementsRequirements TranslatedTranslated

Integrated & Integrated & StandardizedStandardized ImprovementsImprovements

10.10.ImplementImplement SolutionsSolutions

11.11. MonitorMonitor SolutionsSolutions

Action Action PlansPlans

IdentifiedIdentified SolutionsSolutions

Root CausesRoot Causesor Key Factors or Key Factors of Variationof Variation ValidatedValidated

QuantifiedQuantified PerformancePerformance ObjectivesObjectives

6.6.

AnalyzeAnalyze DataData/ID/ID CausesCauses

5. Determine5. Determine PerformancePerformance ObjectivesObjectives

4. Determine4. Determine BaselineBaseline LevelsLevels

Outputs:Outputs:

ProblemProblem StatementStatement

3. Validate3. ValidateMeasuremenMeasurementt

2. Define2. Define CCRCCR && CTQ CTQ

1. Define1. DefineProblemProblem

Steps:Steps:

SolutionsSolutionsImplementedImplemented

12.12.Replicate &Replicate & StandardizeStandardize

ValidatedValidatedMeasurementMeasurement SystemSystem

7. Select7. SelectSolutionsSolutions

6 6 TeamTeam

8. Develop8. Develop ImplementationImplementation Action PlansAction Plans

9. 9. CommunicateCommunicate SolutionsSolutions

BaselinedBaselined CapabilityCapability & Sigma & Sigma LevelsLevels

SolutionsSolutionsCommuni-Communi- cated to Allcated to AllStakeholdersStakeholders

ImprovementsImprovements Validated to Validated to ObjectivesObjectives

V.V.CControlontrol

III.III.AAnalyzenalyze DataData

II.II.MMeasureeasure

IV.IV.IImprovemprove

I.I.DDefineefine

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DEFINING THE PROBLEM CLEARLY DEFINING THE PROBLEM CLEARLY

Not-so-Good ExamplesNot-so-Good Examples Better ExamplesBetter Examples WhyWhy

People complain about People complain about 10% of fuel valve customers 10% of fuel valve customers burrsburrs report burrs at feature XYZ report burrs at feature XYZ

Order entry needs Order entry needs There are too many opportunitiesThere are too many opportunitiesimprovingimproving for errors & delays in the O/E systemfor errors & delays in the O/E system

15% of the splices have15% of the splices have 15% of the splices have wrinkles15% of the splices have wrinkleswrinkles due to cutoff knifewrinkles due to cutoff knife

We have high scrap on shiftWe have high scrap on shift Investigate the causes for the 10%Investigate the causes for the 10%3 due to weak operators3 due to weak operators higher scrap rate on dimensionalhigher scrap rate on dimensional

variation on shift 3variation on shift 3

Be specificBe specific

Be specificBe specific

Avoid causesAvoid causes

Avoid blameAvoid blame

AssignmentAssignment

Write Problem Statement for your projectWrite Problem Statement for your project

The problem should be quantifiable and linkable to a customer expectation.The problem should be quantifiable and linkable to a customer expectation.

COLLECTING STRATIFIED DATA (Contd.) COLLECTING STRATIFIED DATA (Contd.)

No. 70No. 70 of 60of 60 De- 50De- 50fects 40fects 40 3030 20 20 1010 00

No. 70No. 70 of 60of 60 De- 50De- 50fects 40fects 40 3030 20 20 1010 00

L C RL C RSide of PartSide of Part

No. 70No. 70 of 60of 60 De- 50De- 50fects 40fects 40 3030 20 20 1010 00

1 2 31 2 3Machine No.Machine No.

No. 70No. 70 of 60of 60 De- 50De- 50fects 40fects 40 3030 20 20 1010 00

L HL HResin ViscosityResin Viscosity

&&

&&

The more the data can be The more the data can be broken down into groups or by broken down into groups or by variable, the more information variable, the more information is available for diagnosis is available for diagnosis

Here the total defect data is Here the total defect data is broken down by machine broken down by machine number, left/center/right of the number, left/center/right of the part, and low vs high resin part, and low vs high resin viscosityviscosity

Here it appears machine 3 is Here it appears machine 3 is the worse source and the the worse source and the problem shows up mostly on problem shows up mostly on the left side of the part. And, the left side of the part. And, the best resin viscosity is just the best resin viscosity is just below the mid-value.below the mid-value.

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The ProblemThe Problem

Major Major CategoriesCategories

Detail CausesDetail Causes

Sub-causesSub-causes

FISHBONE DIAGRAMFISHBONE DIAGRAM

Use negative wording at detail cause and below levelUse negative wording at detail cause and below level

example nextexample next

FISHBONE DIAGRAM EXAMPLEFISHBONE DIAGRAM EXAMPLE

Lots run out of orderLots run out of order

Procedure not followed

Procedure not followed

Operators not re-tra

ined

Operators not re-tra

inedEasy jobs run firstEasy jobs run first

Supv doesn’t enforce

Supv doesn’t enforce

Doesn’t seemDoesn’t seem importantimportant

Not re

infor

ced b

y mgt

Not re

infor

ced b

y mgt

Opera

tors n

ot moti

vated

Opera

tors n

ot moti

vated

by su

pervi

sors

by su

pervi

sors

Lack of supvLack of supv training training

Loss of LotLoss of LotTraceabilityTraceability

MethodMethod

ManMan MaterialMaterial

MachineMachinei

MULTI-VARI CHARTS (Contd.)MULTI-VARI CHARTS (Contd.)ExampleExample

Source: Motorola 6S BB Week 2 Training Manual Source: Motorola 6S BB Week 2 Training Manual

At 3 different times of the day (8:00, 10:00, and 12:00), 3 consecutive parts At 3 different times of the day (8:00, 10:00, and 12:00), 3 consecutive parts (units 1,2, and 3) are measured at nine positional locations (blue circles) each: (units 1,2, and 3) are measured at nine positional locations (blue circles) each:

What is the biggest source of variation?What is the biggest source of variation? What should you do next? What should you do next? The variation over time (red line) and the The variation over time (red line) and the variation between the 9 locations are much variation between the 9 locations are much smaller than the variation between the 3 unitssmaller than the variation between the 3 units

Investigate why the between-unit variation is Investigate why the between-unit variation is so great, using analytical toolsso great, using analytical tools

Minitab Instructions

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DEFECT-BASED METRICSDEFECT-BASED METRICS

A unit of product can be A unit of product can be defectivedefective if it contains 1 or more if it contains 1 or more defectsdefects

A unit of product can have more than 1 A unit of product can have more than 1 opportunityopportunity to have a defect to have a defect

- Determine all the possible opportunities for problems- Determine all the possible opportunities for problems

- Pare the list down by excluding rare events, grouping - Pare the list down by excluding rare events, grouping similar defect types, and avoiding the trivial similar defect types, and avoiding the trivial

- Define opportunities - Define opportunities consistentlyconsistently between different locations between different locations

Proportion defective (p): Proportion defective (p):

p = no. of defect ive units

tota l n o. of product units

Yield ( YYield ( Y1st-pass1st-pass, or Y, or Yfinalfinal, or RTY, rolled throughput yield):, or RTY, rolled throughput yield): - Y = 1 - p- Y = 1 - p

- The Yield proportion can converted to a sigma The Yield proportion can converted to a sigma value using the Z tables value using the Z tables

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2.00 6.0 3.42.00 6.0 3.4

1.67 5.0 2331.67 5.0 233

1.33 4.0 6,2101.33 4.0 6,210

CACAPAPABIBILILITYTY IMP IMPRROVEOVEMMENTENT

USLUSLLSLLSL

CpCp ppmppm

1.00 3.0 66,8001.00 3.0 66,800

.67 2.0 308,540.67 2.0 308,540

DECISION TREE ON CONFIDENCE INTERVALS DECISION TREE ON CONFIDENCE INTERVALS

For a MeanFor a Mean

with knownwith knownvariance &variance & n n 30 30

with unknownwith unknownvariance, orvariance, or n < 30n < 30

Use Z DistnUse Z DistnConfidence Confidence IntervalInterval

Use t DistnUse t DistnConfidenceConfidenceIntervalInterval

For a VarianceFor a Variance

Use the Use the 22 Distn Distn ConfidenceConfidence IntervalInterval

For a ProportionFor a Proportion

Use Z Distn ConfidenceUse Z Distn ConfidenceInterval if and Interval if and are each are each 5 5

ˆn pˆn q

p. 154p. 154 p. 157p. 157 p. 159p. 159 p. 163p. 163

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skip optional module on confidence intervals

EXERCISE EXERCISE

Assembling two parts together Assembling two parts together

Searching for information Searching for information

Making initial fixture setup Making initial fixture setup

Transporting materials to next station Transporting materials to next station

If test value too high, then to Path B,If test value too high, then to Path B, otherwise to Path A otherwise to Path A

Capturing data once at the source Capturing data once at the source

Examining castings for defects Examining castings for defects

Walking to parts storage for assembly screws Walking to parts storage for assembly screws

Storing a lot on a movable rack Storing a lot on a movable rack Readjusting the fixture setup Readjusting the fixture setup

Trouble-shooting a rejected assembly Trouble-shooting a rejected assembly

QC final inspection QC final inspection

Leaving a form in an in-basket Leaving a form in an in-basket

Attending a benefits Attending a benefits meetingmeeting

R

For each task, check the appropriate symbol.For each task, check the appropriate symbol.