Statistical Models and Control Charts for High-Quality Processes / Edition 1

by Min Xie, Thong Ngee Goh, Vellaisamy Kuralmani

Overview

Control charts are widely used in industry to monitor processes that are far from Zero-Defect (ZD), and their use in a near Zero-Defect manufacturing environment poses many problems. This book presents techniques of using control charts for high-quality processes, and some recent findings and applications of statistical control chart techniques for ZD processes are presented.

A powerful technique based on counting of the cumulative conforming (CCC) items between two nonconforming ones is discussed in detail. Extensions of the CCC chart are described, as well as applications of cumulative sum and exponentially weighted moving average techniques to CCC-related data, multivariate methods, economic design of control chart procedures, and modeling and analysis of trended but regularly adjusted processes.

Many examples, charts, and procedures, are presented throughout the book, and references are provided for those interested in exploring the details. A number of questions and issues are posed for further investigations. Researchers and students may find many ideas in this book useful in their academic work, as a foundation is laid for the exploration of many further theoretical and practical issues.

Product Details

ISBN-13:	9781402070747
Publisher:	Springer US
Publication date:	06/30/2002
Edition description:	2002
Pages:	276
Product dimensions:	6.10(w) x 9.25(h) x 0.24(d)

Table of Contents

Control Charts with Probability Limits.- Cumulative Count of Conforming (CCC) Chart.- Process Improvement Detection.- Modified Implementation of Geometric Chart.- Some Extensions to the Geometric Model.- CUSUM and EWMA Procedures.- Monitoring of Multiple Process Characteristics.- Economic Design of Geometric Chart.- Monitoring and Adjustment of Trended Processes.

Editorial Reviews

Statistical process control based on statistical control charts has been widely used to monitor industrial processes, but has had many problems when used in a near-zero-defects manufacturing environment. Three engineers from Singapore present some recently developed techniques for using control charts to detect process deterioration and possibly to discover process improvement, especially in a near- zero-defect environment. Looking specifically at processes with only occasional problems, they focus on modifying traditional control charts for attributes and one-at-a-time measurements. They also discuss techniques for variable charts and charts based on conventional sampled data. Readers are assumed to be familiar with statistical control charts in general. Annotation c. Book News, Inc., Portland, OR