Process Quality Control: Troubleshooting and Interpretation of Data

Troubleshooting tool for manufacturing processes.A hands-on, solutions-oriented guide, Process QualityControl, Third Edition, by Ellis R, Ott, Edward G.Schilling, and Dean V. Neubauer, gives you a systematicapproach to gathering and analyzing data fortroubleshooting manufacturing processes. This classicemphasizes short term and long term variability, particularly with regard to process capability andperformance. The third edition gives you many newanalytical methods, insights into their application, andcase studies. These techniques include toleranceintervals, a test for the comparison of long term andshort term variation, simplified attribute sample sizedetermination, and an updated discussion of sampling.You'll also find an expanded discussion of control charts, including trend charts, manual adjustment charts, andshort run charts. While the emphasis is on processcontrol, you'll also find significant material on analysis of means.

Table of Contents:
Case HIstories Preface to the Third Edition Preface to the Second Edition Preface to the First Edition Part 1: Basics of Interpretation of Data. 1-Variable Data: An Introduction. 2-Ideas from Time Sequences of Observations. 3-Ideas from Outliers-Variables Data. 4-Variability: Estimating and Comparing. 5-Attributes or Go No-Go Data. Part 2: Statistical Process Control. 6-Sampling to Provide a Feedback of Information. 7-Narrow Limit Gaging in Process Control. 8-On Implementing Statistical Process Control. Part 3: Troubelshooting and Process Improvement. 9-Some Basic Ideas and Methods of Troubleshooting. 10-Some Concepts of Statistical Design of Experiments. 11-Troubleshooting with Attributes Data. 12-Special Strategies in Troubleshooting. 13-Comparing Two Process Averages. 14-Troubleshooting with Variables Data. 15-More than Two Levels of an Independent Variable. 16-What's on the CD. 17-Epilogue. Appendix Tables. Index.

About the Author :
The late Ellis R. Ott was Professor Emeritus of Experimental Statistics at Rutgers, The State University of New Jersey, and the Founding Director of the Rutgers Statistics Center. He received his Ph.D. from the University of Illinois. He consulted extensively including work with the U.S. State Department and the United Nations. Dr. Ott was the recipient of numerous quality control awards, including honorary member of the American Society for Quality and its Brumbaugh Award, the Eugene L. Grant Award, and the Shewhart Medal. He was honored by an award established in his name by the Metropolitan Section of ASQC. Dr. Edward G. Schilling is Professor of Statistics and Director of the Center for Quality and Applied Statistics in the College of Engineering at Rochester Institute of Technology. He was previously manager of the Lighting Quality Operation of the General Electric Company. He received his M.S. and Ph.D. degrees in statistics from Rutgers University, where he studied under Ellis Ott. Dr. Schilling is a fellow of the American Statistical Association and the American Society for Quality, and is the first person to win the American Society for Qualitys Brumbaugh Award four times. He is also a recipient of the Shewhart Medal the Ellis R. Ott Award. He is the author of the Acceptance Sampling Quality Control and was Associate Editor of the 5th Edition of Jurans Quality Handbook. Dean V. Neubauer is employed at Corning Incorporated where he holds the appointed position of Engineering Associate-Statistical Engineering. He is also a member of the adjunct faculty in the Center for Quality and Applied Statistics in the College of Engineering at Rochester Institute of Technology. Mr. Neubauer received his B.S. degree in Statistics from Iowa State University and a M.S. degree in Applied and Mathematical Statistics from Rochester Institute of Technology. He holds two U.S. patents and is an active member of ISO and ASTM standards committees. He is a Fellow and a Charter Statistician of the Royal Statistical Society, a Senior Member and Certified Quality Engineer of the American Society for Quality, and a member of the American Statistical Association.