Statistical Process Control For Quality Improvement- Hardcover Version THE DEMING PARADIGM AND BEYOND SECOND EDITION

The first edition of this groundbreaking text showed that the Statistical Process Control (SPC) paradigm of W. Edwards Deming was not at all the same as the Quality Control paradigm that has dominated American manufacturing since World War II. Its philosophy of good management, to a great extent responsible for the resurgence and success of Japanese manufacturing efforts, is rooted in a paradigm as process-oriented as physics, yet produces a friendly and fulfilling work environment. This second edition broadens its view to reveal even more of Deming's philosophy and provides more techniques for use at the managerial level. It shows readers that CEOs and service industries need SPC at least as much as production lines, and offers precise methods and guidelines for their use.

While the common practice of Quality Assurance aims to prevent bad units from being shipped beyond some allowable proportion, statistical process control (SPC) ensures that bad units are not created in the first place. Its philosophy of continuous quality improvement, to a great extent responsible for the success of Japanese manufacturing, is rooted in a paradigm as process-oriented as physics, yet produces a friendly and fulfilling work environment. The first edition of this groundbreaking text showed that the SPC paradigm of W. Edwards Deming was not at all the same as the Quality Control paradigm that has dominated American manufacturing since World War II. Statistical Process Control: The Deming Paradigm and Beyond, Second Edition reveals even more of Deming's philosophy and provides more techniques for use at the managerial level. Explaining that CEOs and service industries need SPC at least as much as production managers, it offers precise methods and guidelines for their use.Using the practical experience of the authors working both in America and Europe, this book shows how SPC can be implemented in a variety of settings, from health care to manufacturing. It also provides you with the necessary technical background through mathematical and statistical appendices. According to the authors, companies with managers who have adopted the philosophy of statistical process control tend to survive. Those with managers who do not are likely to fail. In which group will your company be?

PREFACESTATISTICAL PROCESS CONTROL: A BRIEF OVERVIEWQuality Control: Origins, MisperceptionsA Case Study in Statistical Process ControlIf Humans Behaved Like MachinesPareto's MaximDeming's Fourteen PointsQC Misconceptions, East and WestWhite Balls, Black BallsThe Basic Paradigm of Statistical Process ControlBasic Statistical Procedures in Statistical Process ControlAcceptance SamplingThe Case for Understanding VariationStatistical CodaACCEPTANCE-REJECTION STATISTICAL PROCESS CONTROLThe Basic TestBasic Test with Equal Lot SizeTesting with Unequal Lot SizesTesting with Open-Ended Count DataTHE DEVELOPMENT OF MEAN AND STANDARD DEVIATION CONTROL CHARTSA Contaminated Production ProcessEstimation of Parameters of the "Norm" ProcessRobust Estimators for Uncontaminated Process ParametersA Process with Mean DriftA Process with Upward Drift in VarianceCharts for Individual MeasurementsProcess CapabilitySEQUENTIAL APPROACHESThe Sequential Likelihood Ratio TestCUSUM Test for Shift of the MeanShewhart CUSUM ChartPerformance of CUSUM Tests on Data with Mean DriftSequential Tests for Persistent Shift of the MeanCUSUM Performance on Data with Upward Variance DriftAcceptance-Rejection CUSUMSEXPLORATORY TECHNIQUES FOR PRELIMINARY ANALYSISThe Schematic PlotSmoothing by ThreesBootstrappingPareto and Ishikawa DiagramsA Bayesian Pareto Analysis for System Optimization of the Space StationThe Management and Planning ToolsOPTIMIZATION APPROACHESA Simplex Algorithm for OptimizationSelection of Objective FunctionMotivation for Linear ModelsMultivariate ExtensionsLeast SquaresModel "Enrichment"Testing for Model "Enrichment"2p Factorial DesignsSome Rotatable Quadratic DesignsSaturated DesignsA Simulation Based ApproachMULTIVARIATE APPROACHESLikelihood Ratio Tests for LocationCompound and Projection TestsA Robust Estimate of "In Control" LocationA Rank Test for Location SlippageA Rank Test for Change in Scale and/or LocationAPPENDICESA Brief Introduction to Linear AlgebraA Brief Introduction to StochasticsStatistical TablesNote: All chapters also include an introduction, references, and problems.

J. Koronacki, J.R. Thompson