Industrial Statistics

1. Front Matter

   Pages I-XVII

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2. Quality Control, Engineering and Monitoring

   1. Front Matter

      Pages 1-1

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   2. Quality Engineering Using Robust Design and Analysis

      • Sung H. Park, Jae J. Kim

      Pages 3-15

   3. The Calibration Problem in Industry

      • C. P. Kitsos, V. L. Ninni

      Pages 17-25

   4. Case Study of Applying Statistical Techniques for the Quality Assurance in a Paint Industry

      • C. Vourvahi, J. Voutsinas, J. Kiriakidis

      Pages 27-49

   5. Taking Multivariate Statistics out into Industry — Multivariate Statistical Progress Control and Process Performance Monitoring

      • Elaine B. Martin, A. Julian Morris

      Pages 51-64

   6. Robust Estimation of Variance Components with High Breakdown Point in the 1-Way Random Effect Model

      • Steffen Uhlig

      Pages 65-73

   7. Sources of Inaccuracy in the Mean and Variance Models for Quality Improvement Problems

      • Ivan N. Vuchkov, Lidia N. Boyadjieva

      Pages 75-86

3. Reliability and Failure Time Analysis

   1. Front Matter

      Pages 87-87

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   2. Accelerated Life Test with Some Parameter Change in Life-Stress Relation

      • Wen-Tao Huang, Huei-Tsan Lin

      Pages 89-97

   3. Accurate Inferences for the Reliability Function Considering Accelerated Life Tests

      • Jorge Alberto Achcar, Jose Carlos Fogo

      Pages 99-109

   4. Prediction of Failures that Have Never Occured: Exponential Case

      • Jaromir Antoch, Josef Machek

      Pages 111-122

   5. Algorithm of Confidence Limits Calculation for the Probability of the Value 1 of a Monotone Boolean Function of Random Variables

      • Alexander M. Andronov

      Pages 123-133

   6. Developing a Graphical Interface for Pre-Posterior Bayesian Analysis

      • P. Erto, A. Lanzotti, M. Staiano

      Pages 135-147

4. Experimental Design

   1. Front Matter

      Pages 149-149

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   2. Nonlinear-Optimal-Sequential Experiment Designs and Applications

      • Christos P. Kitsos

      Pages 151-163

   3. Robust Inference and Experimental Design for Multi-Factor Models

      • Christine H. Müller

      Pages 165-174

   4. Construction of Some New Orthogonal Main-Effect Designs

      • Christos Koukouvinos

      Pages 175-181

   5. Extended V—robustness for Two-level Orthogonal Resolution V Designs

      • Cinzia Mortarino, Luigi Salmaso

      Pages 183-191

   6. Computational Algebraic Geometry in Industrial Experimental Design

      • E. Riccomagno, H. P. Wynn

      Pages 193-198

Devoted to the growing impact of statistical methodology and statistical computing in industry the aim of this book is to link the three components: Statistics - industry - computers. Different areas of industrial statistics are presented by a number of excellent contributions. The following topics are covered: Quality control, engineering and monitoring; reliability and failure time analysis, experimental design; repeated measurements - multiple inference; pharma - statistics; computing, imaging and perception. This book concentrates on the interface between statistical needs in industry and statistical methods developed by statisticians and engineers.

• Analysis
• Excel
• Measure
• Monitoring
• Multivariate statistics
• Permutation
• Random variable
• Session
• Statistical Computing
• Statistical Methods
• Stochastic Processes
• Trend
• actor
• model
• quality assurance

• Department of Statistics, Athens University of Economics and Business, Athens, Greece

  Christos P. Kitsos

• German Cancer Research Center, Biostatistics Unit, Heidelberg, Germany

  Lutz Edler

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