Nonparametric Statistical Process Control

Book description

A unique approach to understanding the foundations of statistical quality control with a focus on the latest developments in nonparametric control charting methodologies

Statistical Process Control (SPC) methods have a long and successful history and have revolutionized many facets of industrial production around the world. This book addresses recent developments in statistical process control bringing the modern use of computers and simulations along with theory within the reach of both the researchers and practitioners. The emphasis is on the burgeoning field of nonparametric SPC (NSPC) and the many new methodologies developed by researchers worldwide that are revolutionizing SPC.

Over the last several years research in SPC, particularly on control charts, has seen phenomenal growth. Control charts are no longer confined to manufacturing and are now applied for process control and monitoring in a wide array of applications, from education, to environmental monitoring, to disease mapping, to crime prevention. This book addresses quality control methodology, especially control charts, from a statistician’s viewpoint, striking a careful balance between theory and practice. Although the focus is on the newer nonparametric control charts, the reader is first introduced to the main classes of the parametric control charts and the associated theory, so that the proper foundational background can be laid. 

  • Reviews basic SPC theory and terminology, the different types of control charts, control chart design, sample size, sampling frequency, control limits, and more
  • Focuses on the distribution-free (nonparametric) charts for the cases in which the underlying process distribution is unknown
  • Provides guidance on control chart selection, choosing control limits and other quality related matters, along with all relevant formulas and tables
  • Uses computer simulations and graphics to illustrate concepts and explore the latest research in SPC

Offering a uniquely balanced presentation of both theory and practice, Nonparametric Methods for Statistical Quality Control is a vital resource for students, interested practitioners, researchers, and anyone with an appropriate background in statistics interested in learning about the foundations of SPC and latest developments in NSPC.

Table of contents

  1. Cover
  2. About the Authors
  3. Preface
  4. About the companion website
  5. 1 Background/Review of Statistical Concepts
    1. Chapter Overview
    2. 1.1 Basic Probability
    3. 1.2 Random Variables and Their Distributions
    4. 1.3 Random Sample
    5. 1.4 Statistical Inference
    6. 1.5 Role of the Computer
  6. 2 Basics of Statistical Process Control
    1. Chapter Overview
    2. 2.1 Basic Concepts
  7. 3 Parametric Univariate Variables Control Charts
    1. Chapter Overview
    2. 3.1 Introduction
    3. 3.2 Parametric Variables Control Charts in Case K
    4. 3.3 Types of Parametric Variables Charts in Case K: Illustrative Examples
    5. 3.4 Shewhart, EWMA, and CUSUM Charts: Which to Use When
    6. 3.5 Control Chart Enhancements
    7. 3.6 Run‐length Distribution in the Specified Parameter Case (Case K)
    8. 3.7 Parameter Estimation Problem and Its Effects on the Control Chart Performance
    9. 3.8 Parametric Variables Control Charts in Case U
    10. 3.9 Types of Parametric Control Charts in Case U: Illustrative Examples
    11. 3.10 Run‐length Distribution in the unknown Parameter Case (Case U)
    12. 3.11 Control Chart Enhancements
    13. 3.12 Phase I Control Charts
    14. 3.13 Size of Phase I Data
    15. 3.14 Robustness of Parametric Control Charts
    16. Some Derivations for the EWMA Control Chart
    17. Markov Chains
    18. Some Derivations for the Shewhart Dispersion Charts
  8. 4 Nonparametric (Distribution‐free) Univariate Variables Control Charts
    1. Chapter Overview
    2. 4.1 Introduction
    3. 4.2 Distribution‐free Variables Control Charts in Case K
    4. 4.3 Distribution‐free Control Charts in Case K: Illustrative Examples
    5. 4.4 Distribution‐free Variables Control Charts in Case U
    6. 4.5 Distribution‐free Control Charts in Case U: Illustrative Examples
    7. 4.6 Effects of Parameter Estimation
    8. 4.7 Size of Phase I Data
    9. 4.8 Control Chart Enhancements
    10. Shewhart Control Charts
    11. \hbox {Appendix 4.2 CUSUM Control Charts
    12. EWMA Control Charts
  9. 5 Miscellaneous Univariate Distribution‐free (Nonparametric) Variables Control Charts
    1. Chapter Overview
    2. 5.1 Introduction
    3. 5.2 Other Univariate Distribution‐free (Nonparametric) Variables Control Charts
  10. Appendix A: Tables
    1. Table A: Binomial distribution – probabilities for the in‐control case
    2. Table B: Probabilities for the Wilcoxon signed‐rank statistic
    3. Table C: Unbiasing charting constants for the construction of normal‐theory variables control charts
    4. Table D1: Cumulative probabilities for the standard normal distribution
    5. Table D2: Cumulative probabilities for the standard normal distribution continued
    6. Table E: Upper tail probabilities for the t distribution
    7. Table F: Upper tail probabilities for the Chi‐square distribution
    8. Table G: Charting constants for the Phase II Shewhart control chart in Case UU for n = 5, varying m, and ARL IC = 370 and 500
    9. Table H: Charting constants for Phase II Shewhart R and S control charts in Case UU with three Phase I estimators of standard deviation for nominal ARL IC values of 370 and 500 with varying m and n = 5, 10 = 5, 10
  11. Appendix BProgrammes
  12. References
  13. Index
  14. End User License Agreement

Product information

  • Title: Nonparametric Statistical Process Control
  • Author(s): Subhabrata Chakraborti, Marien Graham
  • Release date: April 2019
  • Publisher(s): Wiley
  • ISBN: 9781118456033