Description
Taylor & Francis Ltd Statistical Process Control For Real-World Applications 2011 Edition by William A. Levinson
The normal or bell curve distribution is far more common in statistics textbooks than it is in real factories, where processes follow non-normal and often highly skewed distributions. Statistical Process Control for Real-World Applications shows how to handle non-normal applications scientifically and explain the methodology to suppliers and customers.The book exposes the pitfalls of assuming normality for all processes, describes how to test the normality assumption, and illustrates when non-normal distributions are likely to apply. It demonstrates how to handle uncooperative real-world processes that do not follow textbook assumptions. The text explains how to set realistic control limits and calculate meaningful process capability indices for non-normal applications. The book also addresses multivariate systems, nested variation sources, and process performance indices for non-normal distributions.The book includes examples from Minitab (R), StatGraphics (R) Centurion, and MathCAD and covers how to use spreadsheets to give workers a visual signal when an out of control condition is present. The included user disk provides Visual Basic for Applications functions to make tasks such as distribution fitting and tests for goodness of fit as routine as possible. The book shows you how to set up meaningful control charts and report process performance indices that actually reflect the process' ability to deliver quality. Traditional Control ChartsVariation and AccuracyStatistical Hypothesis TestingControl Chart ConceptsSetup and Deployment of Control ChartsInterpretation of x-bar/R and x-bar/s ChartsX (Individual Measurement) ChartsAverage Run Length (ARL)z Chart for Sample Standard Normal DeviatesAcceptance Control ChartWestern Electric Zone TestsProcess Capability and Process PerformanceGoodness-of-Fit TestsMultiple Attribute Control ChartsExercisesSolutionsEndnotesNonnormal DistributionsTransformationsGeneral Procedure for Nonnormal DistributionsThe Gamma DistributionThe Weibull DistributionThe Lognormal DistributionMeasurements with Detection Limits (Censored Data)ExercisesSolutionsEndnotesRange Charts for Nonnormal DistributionsTraditional Range ChartsRange Charts with Exact Control LimitsRange Charts for Nonnormal DistributionsExercisesSolutionsEndnoteNested Normal DistributionsVariance Components: Two Levels of NestingExerciseSolutionProcess Performance IndicesProcess Performance Index for Nonnormal DistributionsConfidence Limits for Normal Process Performance IndicesConfidence Limits for Nonnormal Process Performance IndicesExerciseSolutionEndnotesThe Effect of Gage CapabilityGage Accuracy and VariationGage Capability and Statistical Process ControlGage Capability and Process CapabilityGage Capability and Outgoing QualityExercisesSolutionsMultivariate SystemsMultivariate Normal DistributionMultivariate Control ChartDeployment to a Spreadsheet: Principal Component MethodMultivariate Process Performance IndexControl Charts for the Covariance MatrixEndnotesGlossaryAppendix A: Control Chart FactorsAppendix B: Simulation and ModelingAppendix C: Numerical MethodsReferences