Basic Statistical Tools for Improving Quality

Chang W. Kang

ISBN 10: 0470889497 / ISBN 13: 9780470889497

Published by John Wiley & Sons Inc, 2011

About this Item

This book presents a clear, quick understanding of the basic techniques in statistical quality control that are employed by business and industrial managers alike. Num Pages: 244 pages, Illustrations. BIC Classification: KJMQ. Category: (P) Professional & Vocational. Dimension: 157 x 236 x 13. Weight in Grams: 376. . 2011. 1st Edition. Paperback. . . . . Books ship from the US and Ireland.

Seller Inventory # V9780470889497

Bibliographic Details

• Title: Basic Statistical Tools for Improving Quality
• Publisher: John Wiley & Sons Inc
• Publication Date: 2011
• Language: English
• ISBN 10: 0470889497
• ISBN 13: 9780470889497
• Binding: Soft cover
• Condition: New

About this title

Synopsis

This book is an introductory book on improving the quality of a process or a system, primarily through the technique of statistical process control (SPC). There are numerous technical manuals available for SPC, but this book differs in two ways: (1) the basic tools of SPC are introduced in a no-nonsense, simple, non-math manner, and (2) the methods can be learned and practiced in an uncomplicated fashion using free software (eZ SPC 2.0), which is available to all readers online as a downloadable product. The book explains QC7 Tools, control charts, and statistical analysis including basic design of experiments. Theoretical explanations of the analytical methods are avoided; instead, results are interpreted through the use of the software.

About the Author

Chang W. Kang, PhD, is Professor in the Department of Industrial and Management Engineering at Hanyang University (South Korea). He has published extensively in the areas of engineering statistics, statistical quality control, and quality management. Former president of the Korea Society of Industrial and Systems Engineering, Dr. Kang is the recipient of both the President's Award (2004) and the Medal of Service Merits (2007) by the Korean government.

Paul H. Kvam, PhD, is Professor of Industrial and Systems Engineering at the Georgia Institute of Technology. He has published numerous papers in the areas of statistical reliability with applications to engineering, nonparametric estimation, and analysis of complex and dependent systems. He is a Fellow of the American Statistical Association and the coauthor of Nonparametric Statistics for Science and Engineering (Wiley).