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Statistical Process Control Book

Statistical Process Control
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  • Statistical Process Control
  • Written by author J. R. Thompson
  • Published by Taylor & Francis, Inc., January 2002
  • 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
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Preface
1Statistical Process Control: A Brief Overview1
1.2Quality Control: Origins, Misperceptions3
1.3A Case Study in Statistical Process Control6
1.4If Humans Behaved Like Machines9
1.5Pareto's Maxim10
1.6Deming's Fourteen Points14
1.7QC Misconceptions, East and West19
1.8White Balls, Black Balls21
1.9The Basic Paradigm of Statistical Process Control33
1.10Basic Statistical Procedures in Statistical Process Control34
1.11Acceptance Sampling40
2Acceptance-Rejection SPC51
2.2The Basic Test53
2.3The Basic Test with Equal Lot Size56
2.4Testing with Unequal Lot Sizes61
2.5Testing with Open Ended Count Data66
3The Development of Mean and Standard Deviation Control Charts75
3.2A Contaminated Production Process77
3.3Estimation of Parameters of the "Norm" Process81
3.4Robust Estimators for Uncontaminated Process Parameters90
3.5A Process with Mean Drift96
3.6A Process with Upward Drift in Variance102
3.7Charts for Individual Measurements106
4Sequential Approaches127
4.2The Sequential Likelihood Ratio Test127
4.3CUSUM Test for Shift of the Mean130
4.4Shewhart CUSUM Chart134
4.5Performance of CUSUM Test on Data with Mean Drift137
4.6Sequential Tests for Persistent Shift of the Mean140
4.7CUSUM Performance on Data with Upward Variance Drift157
4.8Acceptance-Rejection CUSUMS161
5Exploratory Techniques for Preliminary Analysis169
5.2The Schematic Plot170
5.3Smoothing by Threes175
6Optimization Approaches189
6.2A Simplex Algorithm for Optimization192
6.3Selection of Objective Function203
6.4Motivation for Linear Models208
6.5Multivariate Extensions219
6.6Least Squares220
6.7Model "Enrichment"200[sic]
6.8Testing for Model "Enrichment"227
6.92[superscript p]Factorial Designs233
6.10Some Rotatable Quadratic Designs238
6.11Saturated Designs245
6.12A Simulation Based Approach246
7Multivariate Approaches257
7.2Likelihood Ratio Tests for Location258
7.3A Compound Test267
7.4A Robust Estimate of "In Control" Location269
7.5A Rank Test for Location Slippage271
7.6A Rank Test for Change in Scale and/or Location275
Appendix A: A Brief Introduction to Linear Algebra283
A.2Elementary Arithmetic286
A.3Linear Independence of Vectors289
A.4Determinants291
A.5Inverses294
A.6Definiteness of a Matrix296
A.7Eigenvalues and Eigenvectors296
A.8Matrix Square Root300
A.9Gram-Schmidt Orthogonalization301
Appendix B: A Brief Introduction to Stochastics303
B.2Conditional Probability309
B.3Random Variables311
B.4Discrete Probability Distributions316
B.5More on Random Variables322
B.6Continuous Probability Distributions325
B.7Laws of Large Numbers335
B.8Moment-Generating Functions337
B.9Central Limit Theorem341
B.10Conditional Density Functions343
B.11Random Vectors344
B.12Poisson Process352
B.13Statistical Inference354
Appendix C: Statistical Tables379
C.1Table of the Normal Distribution380
C.2Table of the X[superscript 2] Distribution381
C.3Table of Student's t Distribution382
C.4Table of the F(.05) Distribution383
C.5Table of the F(.01) Distribution384
C.6Table of the F(.002) Distribution385
C.7Table of the F(.001) Distribution386
Index387


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