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Chapter 12Chapter 12Chapter 12Chapter 12
Design forDesign for
Six SigmaSix Sigma
DFSS ActivitiesDFSS 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
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.
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
Key IdeaKey Idea
Developing a basic functional design involves translating customer requirements into measurable technical requirements and, subsequently, into detailed design specifications.
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Quality Function Quality Function DeploymentDeployment
technicalrequirements
componentcharacteristics
processoperations quality plan
Key IdeaKey Idea
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
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.
Concept EngineeringConcept Engineering
Understanding the customer’s environment.
Converting understanding into requirements.
Operationalizing what has been learned.
Concept generation. Concept selection.
Tools for Design Tools for Design DevelopmentDevelopment
Tolerance designTolerance design Design failure mode and effects Design failure mode and effects
analysisanalysis Reliability predictionReliability prediction
Key IdeaKey Idea
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.
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
Key IdeaKey Idea
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.
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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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
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
Types of ReliabilityTypes of Reliability
Inherent reliabilityInherent reliability – predicted – predicted by product designby product design
Achieved reliabilityAchieved reliability – observed – observed during useduring use
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 failureMean time to failure– Mean time between failuresMean time between failures
Cumulative Failure Rate Cumulative Failure Rate CurveCurve
Key IdeaKey Idea
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.
Failure Rate CurveFailure Rate Curve
“Infant mortality period”
Average Failure RateAverage Failure Rate
Reliability FunctionReliability Function
Probability density function of Probability density function of failures failures
f(t) = f(t) = ee--tt for t > 0 for t > 0 Probability of failure from (0, T) Probability of failure from (0, T)
F(t) = 1 – eF(t) = 1 – e--TT Reliability functionReliability function R(T) = 1 – F(T) = eR(T) = 1 – F(T) = e--TT
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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
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))
Tools for Design Tools for Design OptimizationOptimization
Taguchi loss function Optimizing reliability
Key IdeaKey Idea
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
Taguchi Loss Function Taguchi Loss Function CalculationsCalculations
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 loss function is:
L(x) = 125,000(x - .500)2
Expected loss = k(2 + D2)
where D is the deviation from the target.
Optimizing ReliabilityOptimizing Reliability
StandardizationStandardization RedundancyRedundancy Physics of failurePhysics of failure
Tools for Design Tools for Design VerificationVerification
Reliability testingReliability testing Measurement systems evaluationMeasurement systems evaluation Process capability evaluationProcess capability evaluation
Key IdeaKey Idea
Design verification is necessary to ensure that designs will meet customer requirements and can be produced to specifications.
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)
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.
Metrology - Science of Metrology - Science of MeasurementMeasurement
Accuracy - closeness of agreement between an observed value and a standard
Precision - closeness of agreement between randomly selected individual measurements
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
Repeatability & Repeatability & Reproducibility StudiesReproducibility Studies
Quantify and evaluate the Quantify and evaluate the capability of a measurement capability of a measurement systemsystem– Select m operators and n partsSelect m operators and n parts– Calibrate the measuring instrumentCalibrate the measuring instrument– Randomly measure each part by each Randomly measure each part by each
operator for r trialsoperator for r trials– Compute key statistics to quantify Compute key statistics to quantify
repeatability and reproducibilityrepeatability and reproducibility
Spreadsheet TemplateSpreadsheet Template
R&R EvaluationR&R Evaluation
Under 10% error - OKUnder 10% error - OK 10-30% error - 10-30% error - maymay be OK be OK over 30% error - unacceptableover 30% error - unacceptable
Key IdeaKey Idea
One of the most important functions of metrology is calibration—the comparison of a measurement device or system having a known relation-ship 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
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)
Process Capability StudyProcess Capability Study
1.1. Choose a representative machine or processChoose a representative machine or process
2.2. Define the process conditionsDefine the process conditions
3.3. Select a representative operatorSelect a representative operator
4.4. Provide the right materialsProvide the right materials
5.5. Specify the gauging or measurement methodSpecify the gauging or measurement method
6.6. Record the measurementsRecord the measurements
7.7. Construct a histogram and compute descriptive statistics: mean and standard deviationConstruct a histogram and compute descriptive statistics: mean and standard deviation
8.8. Compare results with specified tolerancesCompare results with specified tolerances
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Process CapabilityProcess Capability
specification specification
specification specification
natural variation natural variation
(a) (b)
natural variation natural variation
(c) (d)
Key IdeaKey Idea
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 =
Spreadsheet TemplateSpreadsheet Template