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1 Chapter 12 Chapter 12 Design for Design for Six Sigma Six Sigma
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Page 1: Chapter 12

11

Chapter 12Chapter 12Chapter 12Chapter 12

Design forDesign for

Six SigmaSix Sigma

Page 2: Chapter 12

DFSS ActivitiesDFSS ActivitiesFour Principal ActivitiesFour Principal Activities

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

Design development, focusing on product and process performance issues necessary to fulfill the product and service requirements in manufacturing or delivery

Design optimization, seeking to minimize the impact of variation in production and use, creating a “robust” design

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

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Key IdeaKey Idea

Like Six Sigma itself, most tools for DFSS have been around for some time; its uniqueness lies in the manner in which they are integrated into a formal methodology, driven by the Six Sigma philosophy, with clear business objectives in mind.

Page 4: Chapter 12

Tools for Concept Tools for Concept DevelopmentDevelopment

Concept development – the process of applying scientific, engineering, and business knowledge to produce a basic functional design that meets both customer needs and manufacturing or service delivery requirements. – Quality function deployment (QFD)– Concept engineering

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Key IdeaKey IdeaConcept DevelopmentConcept Development

Developing a basic functional design involves translating customer requirements into measurable technical requirements and, subsequently, into detailed design specifications.

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Key IdeaKey IdeaQFDQFD

QFD benefits companies through improved communication and teamwork between all constituencies in the value chain, such as between marketing and design, between design and manufacturing, and between purchasing and suppliers.

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House of QualityHouse of Quality

Technical requirements

Voice of the customer

Relationship matrix

Technical requirement priorities

Customerrequirement priorities

Competitive evaluation

Interrelationships

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Quality Function Quality Function DeploymentDeployment

technicalrequirements

componentcharacteristics

processoperations quality plan

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Building the House of Building the House of QualityQuality

1. Identify customer requirements.2. Identify technical requirements.3. Relate the customer requirements to the

technical requirements.4. Conduct an evaluation of competing

products or services.5. Evaluate technical requirements and

develop targets.6. Determine which technical requirements

to deploy in the remainder of the production/delivery process.

Page 11: Chapter 12

Tools for Design Tools for Design DevelopmentDevelopment

Tolerance designTolerance design Design failure mode and effects Design failure mode and effects

analysisanalysis Reliability predictionReliability prediction

Page 12: Chapter 12

Key IdeaKey IdeaTools for Design DevelopmentTools for Design Development

Manufacturing specifications consist of nominal dimensions and tolerances. Nominal refers to the ideal dimension or the target value that manufacturing seeks to meet; tolerance is the permissible variation, recognizing the difficulty of meeting a target consistently.

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Tolerance DesignTolerance Design

Determining permissible variation Determining permissible variation in a dimensionin a dimension

Understand tradeoffs between Understand tradeoffs between costs and performancecosts and performance

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Key IdeaKey IdeaTolerance DesignTolerance Design

Tolerances are necessary because not all parts can be produced exactly to nominal specifications because of natural variations (common causes) in production processes due to the “5 Ms”: men and women, materials, machines, methods, and measurement.

Page 15: Chapter 12

DFMEADFMEA

Design failure mode and effects analysis (DFMEA) – identification of all the ways in which a failure can occur, to estimate the effect and seriousness of the failure, and to recommend corrective design actions.

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DFMEADFMEA

Failure modesFailure modes Effect of the failure on the Effect of the failure on the

customercustomer Severity, likelihood of occurrence, Severity, likelihood of occurrence,

and detection ratingand detection rating Potential causes of failurePotential causes of failure Corrective actions or controlsCorrective actions or controls

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Reliability PredictionReliability PredictionReliability PredictionReliability Prediction

ReliabilityReliability – Generally defined as the ability of a Generally defined as the ability of a

product to perform as expected product to perform as expected over timeover time

– Formally defined as the Formally defined as the probabilityprobability that a product, piece of equipment, that a product, piece of equipment, or system or system performsperforms its intended its intended function for a stated period of function for a stated period of timetime under specified under specified operating conditionsoperating conditions

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Types of FailuresTypes of Failures

Functional failureFunctional failure – failure – failure that occurs at the start of that occurs at the start of product life due to product life due to manufacturing or material manufacturing or material detectsdetects

Reliability failureReliability failure – failure – failure after some period of useafter some period of use

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Types of ReliabilityTypes of Reliability

Inherent reliabilityInherent reliability – predicted – predicted by product designby product design

Achieved reliabilityAchieved reliability – observed – observed during useduring use

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Reliability Measurement Reliability Measurement

Failure rate (Failure rate ()) – number of – number of failures per unit timefailures per unit time

Alternative measuresAlternative measures– Mean time to failure (MTTF)Mean time to failure (MTTF)– Mean time between failures Mean time between failures

(MTBF)(MTBF)

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Cumulative Failure Rate Cumulative Failure Rate CurveCurve

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Failure Rate CurveFailure Rate Curve

“Infant mortality period”

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Average Failure RateAverage Failure Rate

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Key IdeaKey IdeaReliability PredictionReliability Prediction

Many electronic components commonly exhibit a high, but decreasing, failure rate early in their lives (as evidenced by the steep slope of the curve), followed by a period of a relatively constant failure rate, and ending with an increasing failure rate.

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Product Life Product Life Characteristic Curve Characteristic Curve

Three distinct time periodThree distinct time period– Early failureEarly failure– Useful lifeUseful life– Wearout periodWearout period

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Predicting System Predicting System ReliabilityReliability

Series systemSeries system Parallel systemParallel system Combination systemCombination system

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Series SystemsSeries Systems

RS = R1 R2 ... Rn

1 2 n

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Parallel SystemsParallel Systems

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

1

2

n

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Series-Parallel SystemsSeries-Parallel Systems

Convert to equivalent series Convert to equivalent series system system

AA BB

CC

CCDD

RRAA RRBB RRCCRRDD

RRCC

AA BB C’C’ DD

RRAA RRBB RRDD

RRC’C’ = 1 – (1-R = 1 – (1-RCC)(1-R)(1-RCC))

Page 30: Chapter 12

Tools for Design Tools for Design OptimizationOptimization

Taguchi loss function Optimizing reliability

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Key IdeaKey IdeaTools for Design OptimizationTools for Design Optimization

Design optimization includes setting proper tolerances to ensure maximum product performance and making designs robust, that is, insensitive to variations in manufacturing or the use environment.

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Loss FunctionsLoss Functions

loss lossno loss

nominaltolerance

loss loss

Traditional View

Taguchi’s View

Page 33: Chapter 12

Loss functionLoss function

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Taguchi Loss FunctionTaguchi Loss Function

No strict cut-off point divides good No strict cut-off point divides good quality from poor quality. Rather, quality from poor quality. Rather, losses can be approximated by a losses can be approximated by a quadratic function so that larger quadratic function so that larger deviations from target correspond deviations from target correspond to increasingly larger losses.to increasingly larger losses.

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Optimizing ReliabilityOptimizing Reliability

StandardizationStandardization—use components —use components with proven track recordswith proven track records

RedundancyRedundancy—provide backup —provide backup componentscomponents

Physics of failurePhysics of failure—understand —understand physical properties of materialsphysical properties of materials

Page 36: Chapter 12

Tools for Design Tools for Design VerificationVerification

Reliability testingReliability testing Measurement systems evaluationMeasurement systems evaluation Process capability evaluationProcess capability evaluation

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Key IdeaKey IdeaTools for Design VerificationTools for Design Verification

Design verification is necessary to ensure that designs will meet customer requirements and can be produced to specifications.

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Reliability testingReliability testing

Life testingLife testing Accelerated life testingAccelerated life testing Environmental testingEnvironmental testing Vibration and shock testingVibration and shock testing Burn-in (component stress Burn-in (component stress

testing)testing)

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Measurement System Measurement System EvaluationEvaluation

Whenever variation is observed in measurements, some portion is due to measurement system error. Some errors are systematic (called bias); others are random. The size of the errors relative to the measurement value can significantly affect the quality of the data and resulting decisions.

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Metrology - Science of Metrology - Science of MeasurementMeasurement

Accuracy - closeness of agreement between an observed value and a standard – can lead to systematic bias.

Precision - closeness of agreement between randomly selected individual measurements – can lead to random variation.

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Accuracy vs. PrecisionAccuracy vs. Precision

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Repeatability and Repeatability and ReproducibilityReproducibility

Repeatability (equipment Repeatability (equipment variation)variation) – variation in multiple – variation in multiple measurements by an individual measurements by an individual using the same instrument. using the same instrument.

Reproducibility (operator Reproducibility (operator variation)variation) - variation in the same - variation in the same measuring instrument used by measuring instrument used by different individualsdifferent individuals

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Key IdeaKey IdeaCalibrationCalibration

One of the most important functions of metrology is calibration—the comparison of a measurement device or system having a known relationship to national standards against another device or system whose relationship to national standards is unknown.

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Process CapabilityProcess Capability

The range over which the natural The range over which the natural variation of a process occurs as variation of a process occurs as determined by the system of determined by the system of common causescommon causes

Measured by the proportion of Measured by the proportion of output that can be produced output that can be produced within design specificationswithin design specifications

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Process Capability StudyProcess Capability StudyTypical Questions AskedTypical Questions Asked

Where is the process centered?Where is the process centered? How much variability exists in the How much variability exists in the

process?process? Is the performance relative to Is the performance relative to

specs acceptable?specs acceptable? What proportion of output will be What proportion of output will be

expected to meet the specs?expected to meet the specs? What factors contribute to What factors contribute to

variability?variability?

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Types of Capability Types of Capability StudiesStudies

Peak performance studyPeak performance study - how a - how a process performs under ideal conditionsprocess performs under ideal conditions

Process characterization studyProcess characterization study - how a - how a process performs under actual process performs under actual operating conditionsoperating conditions

Component variability studyComponent variability study - relative - relative contribution of different sources of contribution of different sources of variation (e.g., process factors, variation (e.g., process factors, measurement system)measurement system)

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Process CapabilityProcess Capability

specification specification

specification specification

natural variation natural variation

(a) (b)

natural variation natural variation

(c) (d)

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2020 2525 3030 MinutesMinutes

UpperUpperspecification specification

LowerLowerspecificationspecification

NominalNominalvalue value

Process CapabilityProcess Capability

Process is capable

Process distributionProcess distribution

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Process is not capableProcess is not capable

2020 2525 3030 MinutesMinutes

UpperUpperspecification specification

LowerLowerspecificationspecification

NominalNominalvalue value

Process distributionProcess distribution

Process CapabilityProcess Capability

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LowerLowerspecificationspecification

MeanMean

UpperUpperspecification specification

Nominal valueNominal value

Six sigmaSix sigma

Four sigmaFour sigma

Two sigmaTwo sigma

Effects of Reducing Effects of Reducing Variability on Process Variability on Process CapabilityCapability

Page 51: Chapter 12

Key IdeaKey IdeaProcess CapabilityProcess Capability

The process capability index, Cp (sometimes called the process potential index), is defined as the ratio of the specification width to the natural tolerance of the process. Cp relates the natural variation of the process with the design specifications in a single, quantitative measure.

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Process Capability IndexProcess Capability Index

Cp = UTL - LTL 6

Cpl, Cpu }

UTL - 3

Cpl = - LTL 3

Cpk = min{

Cpu =