Statistics in Industry

R. Khattree, C. R. Rao0444506144

Hardbound. This volume presents a state of the art exposition of topics in the industrial statistics. It serves as an invaluable reference for the researchers in industrial statistics/industrial engineering and an up to date source of information for practicing statisticians/industrial engineers. A variety of topics in the areas of industrial process monitoring, industrial experimentation, industrial modelling and data analysis are covered and are authored by leading researchers or practitioners in the particular specialized topic. Targeting the audiences of researchers in academia as well as practitioners and consultants in industry, the book provides comprehensive accounts of the relevant topics. In addition, whenever applicable ample data analytic illustrations are provided with the help of real world data.

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Table of contents :
Handbook of Statistics 22: Statistics in Industry……Page 1
Table of contents……Page 3
Preface……Page 13
Contributors……Page 16
1. Guidelines for Selecting Factors and Factor Levels for an Industrial Designed Experiment……Page 19
2. Industrial Experimentation for Screening……Page 49
3. The Planning and Analysis of Industrial Selection and Screening Experiments……Page 90
4. Uniform Experimental Designs and their Applications in Industry……Page 145
5. Mixed Models and Repeated Measures: Some Illustrative Industrial Examples……Page 185
6. Current Modeling and Design Issues in Response Surface Methodology: GLMs and Models with Block Effects……Page 222
7. A Review of Design and Modeling in Computer Experiments……Page 243
8. Quality Improvement and Robustness via Design of Experiments……Page 274
9. Software to Support Manufacturing Experiments……Page 329
10. Statistics in the Semiconductor Industry……Page 468
11. PREDICT: A New Approach to Product Development and Lifetime Assessment Using Information Integration Technology……Page 508
12. The Promise and Challenge of Mining Web Transaction Data……Page 532
13. Control Chart Schemes for Monitoring the Mean and Variance of Processes Subject to Sustained Shifts and Drifts……Page 559
14. Multivariate Control Charts: Hotelling T2, Data Depth and Beyond……Page 578
15. Effective Sample Sizes for T2 Control Charts……Page 599
16. Multidimensional Scaling in Process Control……Page 612
17. Quantifying the Capability of Industrial Processes……Page 627
18. Taguchi’s Approach to On-line Control Procedure……Page 659
19. Dead-Band Adjustment Schemes for On-line Feedback Quality Control……Page 697
20. Statistical Calibration and Measurements……Page 730
21. Subsampling Designs in Industry: Statistical Inference for Variance Components……Page 764
22. Repeatability, Reproducibility and Interlaboratory Studies……Page 794
23. Tolerancing – Approaches and Related Issues in Industry……Page 822
24. Goodness-of-fit Tests for Univariate and Multivariate Normal Models……Page 865
25. Normal Theory Methods and their Simple Robust Analogs for Univariate and Multivariate Linear Models……Page 903
26. Diagnostic Methods for Univariate and Multivariate Normal Data……Page 953
27. Dimension Reduction Methods Used in Industry……Page 990
28. Growth and Wear Curves……Page 1035
29. Time Series in Industry and Business……Page 1049
30. Stochastic Process Models for Reliability in Dynamic Environments……Page 1101
31. Bayesian Inference for the Number of Undetected Errors……Page 1122
Subject Index……Page 1142
Handbook of Statistics: Contents of Previous Volumes……Page 1156