Statistical Control: By Monitoring and Feedback Adjustment / Edition 1

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Overview

A detailed, practical, accessible guide to efficient statistical control.

Efficient control is a key element in the improvement and maintenance of quality and productivity. This book shows the advantages of bringing together the more commonly used methods of statistical quality control with appropriate techniques of feedback adjustment. It uses recent research and practical experience to provide feedback methods of immediate use in the workplace.

Statistical Control by Monitoring and Feedback Adjustment introduces a new coordinated approach to quality control. The authors' clear and cogent presentation uses extensive graphical explanation supplemented by numerous examples and computational tables. A helpful selection of problems and solutions further facilitates understanding.

Topics covered include:
* A fresh look at process monitoring
* Using feedback adjustment charts
* Minimizing the size of adjustments
* Feedback techniques that minimize costs of adjustment and sampling
* Detection of special causes with Cuscore Statistics
* Efficient monitoring of operating feedback systems
* The roles of models, optimization, and robustness
* A brief review of time series analysis.

Statistical Control by Monitoring and Feedback Adjustment is important reading for quality control engineers and statisticians as well as graduate students in quality control, industrial engineering, and applied statistics.

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Editorial Reviews

From the Publisher
"This book, like all the other works...by Professor George Box, serves a useful purpose, and is a significant addition to the literature on statistical practice...should be of considerable interest to those interested in these topics." (International Journal of Forecasting, No. 16, 2000)

"Box and Luceno have written an interesting and important book. The primary message is that statistical process control (SPC) and engineering process control (EPC) should be used together. ...it is the first book that provides an in-depth treatment of EPC in addition to containing material on SPC." (Journal of Quality Technology)

International Journal of Forecasting
This book, like all the other works...by Professor George Box, serves a useful purpose, and is a significant addition to the literature on statistical practice...should be of considerable interest to those interested in these topics.
International Journal of Forecasting
This book, like all the other works...by Professor George Box, serves a useful purpose, and is a significant addition to the literature on statistical practice...should be of considerable interest to those interested in these topics.
Booknews
Bringing together frequently employed methods of statistical quality control for process monitoring with process adjustment techniques, Box (U. of Wisconsin, Madison) and Luce<~n>o (U. of Cantabria; Santander, Spain) introduce a coordinated approach to efficient "control in a nonstationary world." Quality control engineers, applied statisticians, and graduate students in industrial engineering and related fields should find of value their discussion of control and feedback adjustment charts, modeling process dynamics, costs, and time series analysis. Graphics, exercises, and a normal distribution table supplement the text. Annotation c. by Book News, Inc., Portland, Or.
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Product Details

  • ISBN-13: 9780471190462
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 9/28/1997
  • Series: Wiley Series in Probability and Statistics Series , #337
  • Edition description: Older Edition
  • Edition number: 1
  • Pages: 327
  • Product dimensions: 6.40 (w) x 9.51 (h) x 0.88 (d)

Meet the Author

GEORGE BOX, Director of Research at the University of Wisconsin's Center for Quality and Productivity, is coauthor of a number of books available from Wiley.

ALBERTO LUCE?O is Professor in the ETS de Ingenieros de Caminos at the University of Cantabria Santander, Spain.

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Table of Contents

Control in a Nonstationary World.

Control Charts for Frequencies and Proportions.

Control Charts for Measurement Data.

Modeling Process Dynamics and Forecasting Using Exponential Smoothing.

Time Series Models for Process Disturbances.

Process Adjustment Using Feedback Control: Manual Adjustment Charts.

Control of a Process with Inertia.

Feedback Control When There are Adjustment Costs.

Including the Cost of Surveillance: How Often Should You Sample?

Directed Process Monitoring and Cuscore Charts: Looking for Signals in Noise.

Simultaneous Adjustment and Monitoring.

A Brief Review of Time Series Analysis.

Conclusion.

Three Time Series.

Solutions to Exercises and Problems.

Table A: Normal Distribution Two-Sided Tail Probabilities.

Bibliography.

Index.

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