Statistical Quality Control: Strategies and Tools for Continual Improvement
August 1998, ©1999
The text is written for technique oriented courses on quality like Introduction to Statistical Quality Control/Process Improvement that stress the use of statistical tools.In addition to the statistical tools, the text contains a section (Chapters 2-5) on non-statistical problem solving tools for quality improvement.
The main audience for this book are students in both undergraduate and graduate-level courses on Quality or Quality Control taught in Industrial Engineering programs, Statistics Departments and Schools of Business and Management.Other courses include: Applied Statistical Methods, Engineering Statistics, and Statistics for MBA or Executive MBA programs.This book is also appropriate for use in in-house company training courses on quality.
* Detecting and Prioritizing Problems
* Problem-Solving Strategies
* Group-Based Problem Solving
* The Reward Structure: The Human Side of Problem Solving
* Measurements and Their Importance for Quality
* Analysis of Information: Graphical Displays and Numerical Summaries
* Modeling Variability: An Introduction to Probability Distributions
* Sample Surveys
* Statistical Inference Under Simple Random Sampling
* Acceptance Sampling Plans
* Statistical Process Control: Control Charts
* Process Capability and PRE-Control
* Principles of Effective Experimental Design
* Analysis of Data from Effective Experimental Designs and an Introduction to Factorial Experiments
* Taguchi Design Methods for Product and Process Improvement
* Regression Analysis: A Useful Tool for Modeling Relationships
Dr. Claude W. Burrill is a consultant on quality and project management. He is an Adjunct Professor in the School of Business at the University of Iowa. He received a Ph.D. in Mathematics from the University of Iowa in 1952, and an honorary doctorate from William Patterson College of New Jersey in 1979. His experience includes a year as a Fulbright Scholar at the University of Manchester, UK, ten years as a member of the New York University Graduate Center at Bell Labs, and ten years as a member of the IBM Systems Research Institute. He has held visiting faculty appointments at Columbia University, Dartmouth College, and the National University of Singapore, and has lectured and consulted internationally. He has authored or coauthored eight books on a variety of topics, including mathematics, probability, computer modeling, quality, and project management. He and Professor Ledolter are coauthors of the book Achieving Quality Through Continual Improvement, published by Wiley in 1999.
- Discussion of non-statistical problem solving tools found in Chapters 2-5 covers the organizational aspects of general or team-based problem solving techniques; topics not usually found in other books.
- Thorough coverage of statistical quality control, with emphasis on the understanding of concepts and their practical use in solving quality problems. Coverage of sample inspection plans, control charts and capability indexes includes a careful discussion of the differences between statistical control and capability.
- Extensive discussion of design of experiments for process improvement, from basic principles through the analysis of factorial and fractional factorial designs, concludes with a chapter on Taguchi methods.
- The large collection of exercises for each chapter is supported by Problem Solving Projects at the end of each of the text's five sections. Several of the exercises and Projects involve the analysis of large, case-oriented data sets.