Statistical Process Control: The Deming Paradigm and Beyond 2nd Edition

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?

Table of Contents

PREFACE

STATISTICAL PROCESS CONTROL: A BRIEF OVERVIEW
Quality Control: Origins, Misperceptions
A Case Study in Statistical Process Control
If Humans Behaved Like Machines
Pareto's Maxim
Deming's Fourteen Points
QC Misconceptions, East and West
White Balls, Black Balls
The Basic Paradigm of Statistical Process Control
Basic Statistical Procedures in Statistical Process Control
Acceptance Sampling
The Case for Understanding Variation
Statistical Coda

ACCEPTANCE-REJECTION STATISTICAL PROCESS CONTROL
The Basic Test
Basic Test with Equal Lot Size
Testing with Unequal Lot Sizes
Testing with Open-Ended Count Data

THE DEVELOPMENT OF MEAN AND STANDARD DEVIATION CONTROL CHARTS
A Contaminated Production Process
Estimation of Parameters of the "Norm" Process
Robust Estimators for Uncontaminated Process Parameters
A Process with Mean Drift
A Process with Upward Drift in Variance
Charts for Individual Measurements
Process Capability

SEQUENTIAL APPROACHES
The Sequential Likelihood Ratio Test
CUSUM Test for Shift of the Mean
Shewhart CUSUM Chart
Performance of CUSUM Tests on Data with Mean Drift
Sequential Tests for Persistent Shift of the Mean
CUSUM Performance on Data with Upward Variance Drift
Acceptance-Rejection CUSUMS

EXPLORATORY TECHNIQUES FOR PRELIMINARY ANALYSIS
The Schematic Plot
Smoothing by Threes
Bootstrapping
Pareto and Ishikawa Diagrams
A Bayesian Pareto Analysis for System Optimization of the Space Station
The Management and Planning Tools

OPTIMIZATION APPROACHES
A Simplex Algorithm for Optimization
Selection of Objective Function
Motivation for Linear Models
Multivariate Extensions
Least Squares
Model "Enrichment"
Testing for Model "Enrichment"
2p Factorial Designs
Some Rotatable Quadratic Designs
Saturated Designs
A Simulation Based Approach

MULTIVARIATE APPROACHES
Likelihood Ratio Tests for Location
Compound and Projection Tests
A Robust Estimate of "In Control" Location
A Rank Test for Location Slippage
A Rank Test for Change in Scale and/or Location

APPENDICES
A Brief Introduction to Linear Algebra
A Brief Introduction to Stochastics
Statistical Tables

Note: All chapters also include an introduction, references, and problems.

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