Process Quality Control : Troubleshooting and Interpretation of Data, 4th Edition

Ellis Ott taught generations of quality practitioners to be explorers of the truth through the collection and graphical portrayal of data. From a simple plea to "plot the data" to devising a graphical analytical tool called the analysis of means (ANOM), Ott demonstrated that process knowledge is to be gained by seeking the information contained within the data.

In this newest version of Ott's classic text, the authors have strived to continue down the path that he created for others to follow. Additions to this revised edition include: the use of dot plots as an alternative to histograms; digidot plots; adding events to charts; emphasis on the role that acceptance control charts play in controlling risks and the computation of average run length (ARL); a new chapter devoted to process capability, process performance, and process improvement, including the use of confidence intervals for process capability metrics; narrow-limit gauging as another means of assessing the capability of a process; Six Sigma methodology; design resolution; scatter plot matrices as applied to datasets of higher dimensions; and a new chapter on measurement studies.

List of Figures and Tables
Case Histories
Preface to the Fourth Edition
Preface to the Third Edition
Preface to the Second Edition
Preface to the First Edition

Part 1 :  Basics of Interpretation of Data
Chapter 1 : Variables Data : An Introduction
Chapter 2 : Ideas from Time Sequences of Observations
Chapter 3 : Ideas from Outliers - Variables Data
Chapter 4 : Variability - Estimating and Comparing
Chapter 5 : Attributes or Go No-Go Data

Part 2 : Statistical Process Control
Chapter 6 : Sampling and Narrow-Limit Gauging
Chapter 7 : Principles and Applications of Control Charts
Chapter 8 : Process Capability, Performance and Improvement

Part 3 : Troubleshooting and Process Improvement
Chapter 9 : Some Basic Ideas and Methods of Troubleshooting and Problem Solving
Chapter 10 : Some Concepts of Statistical Design of Experiments
Chapter 11 : Troubleshooting with Attributes Data
Chapter 12 : Special Strategies in Troubleshooting
Chapter 13 : Comparing Two Process Averages
Chapter 14 : Troubleshooting with Variables Data
Chapter 15 : More Than Two Levels of an Independent Variable
Chapter 16 : Assessing Measurements as a Process
Chapter 17 : What’s on the CD
Chapter 18 : Epilogue

Appendix Tables
Index