Ch12_Design for Six Sigma

7/28/2019 Ch12_Design for Six Sigma

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02/25/06 SJSU Bus. 142 - David Bentley 1

Chapter12 Design for SixSigma (DFSS)

QFD, Reliability analysis, Taguchi

loss function, Process capability


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DFSS Activity Categories Concept development

Design development

Design optimization

Design verification

Well look at each of these in detail


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Concept Development Based on:

Customer requirements

Technological capabilities Economic considerations

Tools Quality Function Deployment (QFD) Concept engineering


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Rev. 11/25/02 SJSU Bus. 142 - David Bentley 4

Quality Function Deployment

(QFD) Structured approach for design Developed at Mitsubishis Kobe shipyards

House of quality built on relationships Customer requirements Design requirements Competitive assessment Technical assessment

4 layers: product, part, process, production(quality plans)


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The House of QualityCorrelation

matrix

Designrequirements

Customer

require-

ments

Competitive

assessment

Relationship

matrix

Specifications

or

target values

Operations Management, Seventh Edition, by William J. Stevenson

Copyright 2002 by The McGraw-Hill Companies, Inc. All rights reserved.


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SJSU Bus. 142 - David Bentley 6

House of Quality

Technical requirements

Voice of

the

customer

Relationship

matrix

Technical requirement

priorities

Customer

requirement

priorities

Competitive

evaluation

Interrelationships

THE MANAGEMENT AND CONTROL OF QUALITY, 5e, 2002 South-Western/Thomson Learning TM


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11/21/02 SJSU Bus 142 - David Bentley 7

QFD Example

Customer

Requirements

Easy to closeStays open on a hill

Easy to open

Doesnt leak in rain

No road noise

Importance weighting

Engineering

Characteristics

Energyneeded

toclosedoor

Checkforce

onlevel

ground

Energyneeded

toopendoor

Waterresistance

10 6 6 9 2 3

75

3

3

2

X

X

X

X

X

Correlation:

Strong positivePositive

NegativeStrong negative

X*

Competitive evaluation

X = UsA = Comp. AB = Comp. B(5 is best)

1 2 3 4 5

X AB

X AB

XAB

A X B

X A B

Relationships:

Strong = 9

Medium = 3

Small = 1Target values

Reduceenergy

levelto7.5f

t/lb

Reduceforce

to9lb.

Reduceenergy

to7.5

ft/lb.

Maintain

currentlevel

Technical evaluation

(5 is best)

54321

B

A

X

BA

X B

A

X

B

X

A

BXABA

X

Doorseal

resistance

Accoust.Trans.

Window

Maintain

currentlevel

Maintain

currentlevel

Operations Management, Seventh Edition, by William J. Stevenson

Copyright 2002 by The McGraw-Hill Companies, Inc. All rights reserved.


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QFD Steps - 11. Identify/ prioritize customer

requirements

2. Determine technical requirements

3. Relate customer requirements totechnical requirements

4. Compare ability to meet requirementsagainst competitive products


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QFD Steps - 25. Set targets for technical requirements

and determine capability

6. Look for high opportunityrequirements to satisfy customer

7. Continue QFD process to the next

level.


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QFD Levels

technical

requirements

component

characteristics

process

operationsquality plan



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Concept Engineering Understand customer environment

Convert into requirements

Deploy learning into operations

Generate concepts

Select appropriate concept


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Design Development Product and process performance issues

Focus on ability to meet requirements in

operations Tools

Tolerance design and process capability

Design failure mode and effects analysis(DFEA)

Reliability prediction


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Tolerance Design -1

Specification Translation of customer requirements into design

requirements

Consists of nominal value and tolerances

Nominal value Ideal dimension or target value for meeting customer

requirement

Tolerance Allowable variation above and/or below nominal value

Recognizes natural variation (common causes)


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Tolerance Design -2

Consider tradeoff between costs andperformance

Too tight tolerances = unnecessary cost

Too loose tolerances = not meetingcustomer requirements

End result: too loose or too tight is goingto cost you money!


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DFMEA Design failure and effects analysis (DFMEA)

Identify all the ways failures can occur

Estimate effects of the failures

Recommend changes in design

THE MANAGEMENT AND CONTROL OF QUALITY 5 2002 S h W /Th L i TM


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THE MANAGEMENT AND CONTROL OF QUALITY 5 2002 S th W t /Th L i TM


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Reliability Prediction Generally defined as the ability of a product

to perform as expected over time

Formally defined as the probability that aproduct, piece of equipment, or systemperforms its intended function for a stated

period oftime under specified operatingconditions


THE MANAGEMENT AND CONTROL OF QUALITY 5 2002 S th W t /Th L i TM (M d 11/11/02 DAB)


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Types of Failures

Functionalfailure

Failure that occurs at the start of product life

due to manufacturing or material detectsDOA or

infant mortality

Reliabilityfailure Failure after some period of use

THE MANAGEMENT AND CONTROL OF QUALITY, 5e, 2002 South-Western/Thomson Learning TM (Mod 11/11/02 DAB)

THE MANAGEMENT AND CONTROL OF QUALITY 5e 2002 South Western/Thomson Learning TM (Mod 11/11/02 DAB)


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Types of Reliability

Inherentreliability predicted byproduct design (robust design)

Achievedreliability observed duringuse


THE MANAGEMENT AND CONTROL OF QUALITY 5e 2002 South Western/Thomson Learning TM


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Reliability Measurement

Failurerate(l) number of failures perunit time

Alternative measures

Mean time to failure

Mean time between failures


THE MANAGEMENT AND CONTROL OF QUALITY 5e 2002 South Western/Thomson Learning TM


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Cumulative Failure Rate Curve

THE MANAGEMENT AND CONTROL OF QUALITY, 5e, 2002 South-Western/Thomson Learning

THE MANAGEMENT AND CONTROL OF QUALITY 5e 2002 South-Western/Thomson Learning TM


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Failure Rate Curve

Infant

mortality

period

THE MANAGEMENT AND CONTROL OF QUALITY, 5e, 2002 South-Western/Thomson Learning

THE MANAGEMENT AND CONTROL OF QUALITY 5e 2002 South-Western/Thomson Learning TM


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Average Failure Rate

THE MANAGEMENT AND CONTROL OF QUALITY, 5e, 2002 South Western/Thomson Learning



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Reliability Function

Probability density function of failuresf(t) = le-lt for t > 0

Probability of failure from (0, T)

F(t) = 1 e-lT Reliability function

R(T) = 1 F(T) = e-lT

THE MANAGEMENT AND CONTROL OF QUALITY, 5e, 2002 South Western/Thomson Learning



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Series Systems

RS = R1 R2 ... Rn

1 2 n

N G N N CON O O QU , 5e, 00 Sout Weste / o so ea g



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Parallel Systems

RS = 1 - (1 - R1) (1 - R2)... (1 - Rn)

1

2

n

Q , , g



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Series-Parallel Systems

Convert to equivalent series system

A B

C

C

D

RA RB RCRD

RC

A B C D

RA RB RD

RC = 1

(1-RC)(1-RC)

Q , , g


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Design optimization

Minimize variation in processes

Seek robust design (Taguchi)

Insensitive to process variations or the useenvironment

Tools

Taguchi loss function

Optimizing reliability



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Loss Functions

loss lossno loss

nominaltolerance

loss loss

Tradit ional

View

Taguchis

View



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Taguchi Loss FunctionCalculations

L(x) = k(x - T)2

Example: Specification = .500 .020

Failure outside of the tolerance range costs $50to repair. Thus, 50 = k(.020)2. Solving for k

yields k = 125,000. The loss function is:

L(x) = 125,000(x - .500)2

Expected loss = k(2 + D2) where D is the deviation

from the target.



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Optimizing Reliability

Standardization

Redundancy

Physics of failure


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Design Verification

Ensure that process capability meets theappropriate sigma level

Meet specifications (AND customerrequirements)

Tools

Reliability testing Measurement systems evaluation

Process capability determination



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Reliability Testing

Life testing

Accelerated life testing

Environmental testing

Vibration and shock testing

Burn-in


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Measurement SystemEvaluation

Variation can be due to:

Process variation

Measurement system error Random

Systematic (bias)

A combination of the two


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Metrology- 1

Definition: The Science of Measurement

Accuracy

How close an observation is to a standard

Precision

How close random individual

measurements are to each other


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Metrology - 2

Repeatability

Instrument variation

Variation in measurements using sameinstrument and same individual

Reproducibility

Operator variationVariation in measurements using same

instrument and different individual


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R&R Studies

Select m operators and n parts

Calibrate the measuring instrument

Randomly measure each part by eachoperator for r trials

Compute key statistics to quantifyrepeatability and reproducibility


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R&R Spreadsheet Template


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R&R Evaluation

Acceptable: < 10%

Unacceptable: > 30%

Questionable: 10-30%


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Calibration

Compare 2 instruments or systems

1 with known relationship to national

standards 1 with unknown relationship to national

standards


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Process Capability

The range over which the natural variation of aprocess occurs as determined by the system of

common causes Measured by the proportion of output that can be

produced within design specifications


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Types of Capability Studies

PeakperformancestudyHow a process performs under ideal

conditions ProcesscharacterizationstudyHow a process performs under actualoperating conditions

ComponentvariabilitystudyRelative contribution of different sources ofvariation (e.g., process factors, measurement

system)


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Process Capability Study

Choose a representative machine or process Define the process conditions Select a representative operator Provide the right materials Specify the gauging or measurement method Record the measurements

Construct a histogram and compute descriptivestatistics: mean and standard deviation Compare results with specified tolerances


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Process Capability

specification specification

specification specification

natural variation natural variation

(a) (b)

natural variation natural variation

(c) (d)


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Process Capability Index

Cp =UTL - LTL

6

Cpl, Cpu }

UTL - m3

Cpl =m - LTL

3

Cpk = min{

Cpu =


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Process Capability Ratios

Non-centered process (general case):

choose cpk= the lower of:

Upper spec process meancpu = ---------------------------------- or

3

Process mean lower speccpl = ----------------------------------

3SJSU Bus. 142 David A. Bentley 09/30/02


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Process Capability Ratios

Centered process (special case):

specification width

cp = ----------------------------process width

Upper spec lower spec

= ------------------------------

6SJSU Bus. 142 David A. Bentley 09/16/02


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Process Capability

Requirements Process must be normally distributed

Process must be in control

Process capability result:

> 1.34 = capable

< 1.33 = not capable

= 1.33 = barely capable

> 5 or 10 is overkill, excessive resource use

SJSU Bus. 142 David A. Bentley 0/24/06


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Process CapabilitySpreadsheet Template

Ch12_Design for Six Sigma

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