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.

"Full of numerous case studies that give insight into the kind of detailed process sleuthing that process capability studies are all about ... it should be a part of every serious quality practitioner's library."

--Bert Gunter in Quality Progress Magazine* Want to design fail-safe methods for finding and solving problems in complex processes? Discover new ways to coax answers from complicated data? Uncover hidden value in perplexing findings? If you want the most sophisticated and insightful approach to process sleuthing and process capability available, you've come to the right place. Packed with case studies drawn from real industrial processes, Process Quality Control demonstrates how to collect, crunch, and analyze data, step by step. Along the way, it gives you examples of successful, real-world applications used to solve tough questions. This book can help you: Learn time-tested troubleshooting methodologies. Discover better ways to gather, interpret and analyze data. Correctly interpret findings with time-ordered data. Resolve difficult, puzzling, or conflicting results with proven methods. Gain new insight in the analysis of attributes and variables data. Employ newer methods of analysis to maximize the information from your data. Draw problem-solving solutions from the identification of outliers in data. Apply graphical analysis to experimental designs. For anyone charged with discovering problems in processes, or suggesting improvements, there could be no more worthwhile--or inspiring--reading than Ellis Ott's, Edward G. Schilling's, and Dean V. Neubauer's Process Quality Control.