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Statistical Process Control For Quality Improvement- Hardcover Version 2nd edition [Hardback]

(Rice University, Houston, Texas, USA),
  • Format: Hardback, 454 pages, height x width: 234x156 mm, weight: 816 g, 144 Illustrations, black and white
  • Pub. Date: 26-Dec-2001
  • Publisher: Chapman & Hall/CRC
  • ISBN-10: 1584882425
  • ISBN-13: 9781584882428
  • Hardback
  • Price: 245,80 €
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  • Format: Hardback, 454 pages, height x width: 234x156 mm, weight: 816 g, 144 Illustrations, black and white
  • Pub. Date: 26-Dec-2001
  • Publisher: Chapman & Hall/CRC
  • ISBN-10: 1584882425
  • ISBN-13: 9781584882428
A textbook for a graduate or advanced undergraduate course; some individual chapters have also been used for short industrial courses in Texas and Poland by Thompson (statistics, Rice U.) and Koronacki (artificial intelligence, Polish Academy of Sciences). To the statistical methods used in industrial process control, they add a mathematical modeling background. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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?

Reviews

From the first edition: "The book is intellectually stimulating, sometimes on non-statistical issues, which is a rare bonus for readers in this field." - Bulletin of the International Statistical Institute, Short Book Reviews

Preface to First Edition ix
Preface to Second Edition xix
Statistical Process Control: A Brief Overview
1(52)
Introduction
1(2)
Quality Control: Origins, Misperceptions
3(3)
A Case Study in Statistical Process Control
6(3)
If Humans Behaved Like Machines
9(1)
Pareto's Maxim
10(4)
Deming's Fourteen Points
14(4)
QC Misconceptions, East and West
18(2)
White Balls, Black Balls
20(12)
The Basic Paradigm of Statistical Process Control
32(1)
Basic Statistical Procedures in Statistical Process Control
33(6)
Acceptance Sampling
39(2)
The Case for Understanding Variation
41(4)
Statistical Coda
45(8)
References
47(1)
Problems
48(5)
Acceptance-Rejection SPC
53(22)
Introduction
53(2)
The Basic Test
55(3)
Basic Test with Equal Lot Size
58(5)
Testing with Unequal Lot Sizes
63(4)
Testing with Open-Ended Count Data
67(8)
Problems
71(4)
The Development of Mean and Standard Deviation Control Charts
75(54)
Introduction
75(2)
A Contaminated Production Process
77(4)
Estimation of Parameters of the ``Norm'' Process
81(9)
Robust Estimators for Uncontaminated Process Parameters
90(5)
A Process with Mean Drift
95(5)
A Process with Upward Drift in Variance
100(4)
Charts for Individual Measurements
104(14)
Process Capability
118(11)
References
123(1)
Problems
123(6)
Sequential Approaches
129(42)
Introduction
129(1)
The Sequential Likelihood Ratio Test
129(3)
CUSUM Test for Shift of the Mean
132(4)
Shewhart CUSUM Chart
136(2)
Performance of CUSUM Tests on Data with Mean Drift
138(3)
Sequential Tests for Persistent Shift of the Mean
141(17)
CUSUM Performance on Data with Upward Variance Drift
158(4)
Acceptance-Rejection CUSUMs
162(9)
References
165(1)
Problems
166(5)
Exploratory Techniques for Preliminary Analysis
171(54)
Introduction
171(1)
The Schematic Plot
172(5)
Smoothing by Threes
177(9)
Bootstrapping
186(7)
Pareto and Ishikawa Diagrams
193(4)
A Bayesian Pareto Analysis for System Optimization of the Space Station
197(9)
The Management and Planning Tools
206(19)
References
219(1)
Problems
220(5)
Optimization Approaches
225(64)
Introduction
225(3)
A Simplex Algorithm for Optimization
228(9)
Selection of Objective Function
237(5)
Motivation for Linear Models
242(10)
Multivariate Extensions
252(1)
Least Squares
253(5)
Model ``Enrichment''
258(2)
Testing for Model ``Enrichment''
260(6)
2p Factorial Designs
266(4)
Some Rotatable Quadratic Designs
270(6)
Saturated Designs
276(2)
A Simulation Based Approach
278(11)
References
281(1)
Problems
282(7)
Multivariate Approaches
289(32)
Introduction
289(1)
Likelihood Ratio Tests for Location
290(12)
Compound and Projection Tests
302(3)
A Robust Estimate of ``In Control'' Location
305(3)
A Rank Test for Location Slippage
308(4)
A Rank Test for Change in Scale and/or Location
312(9)
References
316(1)
Problems
317(4)
Appendix A: A Brief Introduction to Linear Algebra 321(18)
A.1. Introduction
321(2)
A.2. Elementary Arithmetic
323(4)
A.3. Linear Independence of Vectors
327(1)
A.4. Determinants
328(3)
A.5. Inverses
331(2)
A.6. Definiteness of a Matrix
333(1)
A.7. Eigenvalues and Eigenvectors
333(4)
A.8. Matrix Square Root
337(1)
A.9. Gram-Schmidt Orthogonalization
338(1)
Appendix B: A Brief Introduction to Stochastics 339(82)
B.1 Introduction
339(5)
B.2. Conditional Probability
344(2)
B.3. Random Variables
346(5)
B.4. Discrete Probability Distributions
351(5)
B.5. More on Random Variables
356(4)
B.6. Continuous Probability Distributions
360(10)
B.7. Laws of Large Numbers
370(2)
B.8. Moment-Generating Functions
372(4)
B.9. Central Limit Theorem
376(1)
B.10. Conditional Density Functions
377(1)
B.11. Random Vectors
378(9)
B.12. Poisson Process
387(1)
B.13. Statistical Inference
388(23)
B.14. Bayesian Statistics
411(10)
References
420(1)
Appendix C: Statistical Tables 421(6)
C.1 Table of the Normal Distribution
422(1)
C.2. Table of the Chi-Square Distribution
423(1)
C.3. Table of Student's t Distribution
424(1)
C.4. Table of the F Distribution with α = .05
425(1)
C.5. Table of the F Distribution with α = .01
426(1)
Index 427
J. Koronacki, J.R. Thompson