5. design for six sigma

8/3/2019 5. Design for Six Sigma

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Chapter 12

Design for

Six Sigma


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DFSS Activities

Concept development, determining productfunctionality based upon customer requirements,technological capabilities, and economic realities

Design development, focusing on product andprocess performance issues necessary to fulfill theproduct and service requirements in manufacturingor delivery

Design optimization, seeking to minimize the impactof variation in production and use, creating arobust design

Design verification, ensuring that the capability ofthe production system meets the appropriate sigma

level


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Key Idea

Like Six Sigma itself, most tools for DFSS havebeen around for some time; its uniqueness lies in

the manner in which they are integrated into aformal methodology, driven by the Six Sigmaphilosophy, with clear business objectives inmind.


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Tools for Concept

Development Concept development the process of

applying scientific, engineering, and

business knowledge to produce a basicfunctional design that meets both customerneeds and manufacturing or service deliveryrequirements.

Quality function deployment (QFD) Concept engineering


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Key Idea

Developing a basic functional design involvestranslating customer requirements into

measurable technical requirements and,subsequently, into detailed designspecifications.


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Quality Function

Deployment

technicalrequirements

componentcharacteristics

processoperations quality plan


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Key Idea

QFD benefits companies through improvedcommunication and teamwork between all

constituencies in the value chain, such asbetween marketing and design, betweendesign and manufacturing, and betweenpurchasing and suppliers.


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House of Quality

Technical requirements

Voice ofthe

customer

Relationshipmatrix

Technical requirementpriorities

Customerrequirement

priorities

Competitiveevaluation

Interrelationships


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Building the House of

Quality1. Identify customer requirements.

2. Identify technical requirements.

3. Relate the customer requirements to thetechnical requirements.

4. Conduct an evaluation of competingproducts or services.

5. Evaluate technical requirements anddevelop targets.

6. Determine which technical requirements todeploy in the remainder of the

production/delivery process.


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Concept Engineering

Understanding the customersenvironment.

Converting understanding intorequirements.

Operationalizing what has been

learned. Concept generation.

Concept selection.


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Tools for Design

Development Tolerance design

Design failure mode and effects

analysis

Reliability prediction


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Key Idea

Manufacturing specifications consist of nominaldimensions and tolerances. Nominalrefers to

the ideal dimension or the target value thatmanufacturing seeks to meet; toleranceis thepermissible variation, recognizing the difficultyof meeting a target consistently.


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Tolerance Design

Determining permissible variation in adimension

Understand tradeoffs between costsand performance


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Key Idea

Tolerances are necessary because not allparts can be produced exactly to nominal

specifications because of natural variations(common causes) in production processesdue to the 5 Ms: men and women,materials, machines, methods, and

measurement.


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DFMEA

Design failure mode and effects analysis(DFMEA) identification of all the ways inwhich a failure can occur, to estimate the effectand seriousness of the failure, and torecommend corrective design actions.


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Reliability Prediction

Reliability

Generally defined as the ability of a

product to perform as expected overtime

Formally defined as the probability that a

product, piece of equipment, or systemperforms its intended function for astated period oftime under specifiedoperating conditions


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Types of Failures

Functional failure failure thatoccurs at the start of product life

due to manufacturing or materialdetects

Reliability failure failure aftersome period of use


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Types of Reliability

Inherent reliability predicted byproduct design

Achieved reliability observedduring use


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Reliability Measurement

Failure rate (l) number offailures per unit time

Alternative measures

Mean time to failure

Mean time between failures


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Cumulative Failure RateCurve


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Key Idea

Many electronic components commonlyexhibit a high, but decreasing, failure rate

early in their lives (as evidenced by the steepslope of the curve), followed by a period of arelatively constant failure rate, and endingwith an increasing failure rate.


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Failure Rate Curve

Infant

mortality

period


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Average Failure Rate


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Reliability Function

Probability density function offailures

f(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


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Series Systems

RS = R1 R2 ... Rn

1 2 n


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Parallel Systems

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

1

2

n


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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)


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Tools for DesignOptimization

Taguchi loss function

Optimizing reliability


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Key Idea

Design optimization includes settingproper tolerances to ensure maximum

product performance and makingdesigns robust, that is, insensitive tovariations in manufacturing or the use

environment.


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Loss Functions

loss lossno loss

nominaltolerance

loss loss

Traditional

View

Taguchis

View

T hi L F i


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Taguchi Loss FunctionCalculations

Loss function: L(x) = k(x - T)2

Example: Specification = .500 .020. Failure outside

of the tolerance range costs $50 to repair. Thus, 50 =k(.020)2. Solving for k yields k = 125,000. The lossfunction 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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Tools for Design Verification

Reliability testing

Measurement systems evaluation

Process capability evaluation


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Key Idea

Design verification is necessary toensure that designs will meet customer

requirements and can be produced tospecifications.


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Reliability testing

Life testing

Accelerated life testing

Environmental testing

Vibration and shock testing

Burn-in (component stress testing)


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Measurement SystemEvaluation

Whenever variation is observed inmeasurements, some portion is due to

measurement system error. Some errorsare systematic (called bias); others arerandom. The size of the errors relative tothe measurement value can significantly

affect the quality of the data andresulting decisions.


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Metrology - Science ofMeasurement

Accuracy - closeness of agreementbetween an observed value and a

standard Precision - closeness of agreement

between randomly selected individual

measurements


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Repeatability andReproducibility

Repeatability (equipment variation)variation in multiple measurements by

an individual using the sameinstrument.

Reproducibility (operator variation) -

variation in the same measuringinstrument used by differentindividuals


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Repeatability &Reproducibility Studies

Quantify and evaluate the capability ofa measurement system

Select m operators and n parts Calibrate the measuring instrument

Randomly measure each part by each

operator for r trials Compute key statistics to quantify

repeatability and reproducibility


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Spreadsheet Template


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R&R Evaluation

Under 10% error - OK

10-30% error - maybe OK

over 30% error - unacceptable


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Key Idea

One of the most important functions ofmetrology is calibrationthe

comparison of a measurement deviceor system having a known relation-shipto national standards against another

device or system whose relationship tonational standards is unknown.


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Process Capability

The range over which the naturalvariation of a process occurs as

determined by the system of commoncauses

Measured by the proportion of output

that can be produced within designspecifications


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Types of Capability Studies

Peak performance study- how a processperforms under ideal conditions

Process characterization study- how aprocess performs under actual operatingconditions

Component variability study- relative

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


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Process Capability Study

1. Choose a representative machine or process

2. Define the process conditions

3. Select a representative operator4. Provide the right materials

5. Specify the gauging or measurement method

6. Record the measurements

7. Construct a histogram and computedescriptive statistics: mean and standarddeviation

8. 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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Key Idea

The process capability index, Cp(sometimes called the process potential

index), is defined as the ratio of thespecification width to the naturaltolerance of the process. Cp relates the

natural variation of the process with thedesign specifications in a single,quantitative measure.


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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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Spreadsheet Template

5. design for six sigma

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