[.ca] Process Quality Control: Troubleshooting And ... (ISBN 0873896556)

Great book.:
You want SPC, you got it.

Great Statistical/Process Engineering Reference:
This is a wonderful textbook for the practicing statistician, process engineer, or anyone who works with data on a regular basis. This book finds the right mix of statistical theory and practical applications of the statistical concepts to process troubleshooting. "Process Quality Control: Troubleshooting and Interpretation of Data" will be appropriate for a course taught to statistics majors as well as anyone in an engineering field, and it will also be a very valuable reference to anyone working in industry who is tasked with using data to make decisions about their processes. The book is very thorough, covering everything from the basics of visualizing data (histograms, box plots, etc.) through basic DOE and SPC all the way to more sophisticated SPC concepts such as narrow-limit gauging, acceptance control charts, and cumulative sum charts. I cannot think of a topic in basic SPC that is not covered in this text. A great bonus is the CD that comes with the text that includes answers to all of the exercises and an add-in for Excel that performs Analysis of Means, making this great graphical tool for summarizing results of statistical analyses even more practical to use. All in all, a very thorough text with many examples/case studies that would be useful to anyone in industry in charge of controlling and improving processes.

An Updated Classic:
One of my prize possessions is this book, a copy of the original 1975 edition, signed by Professor Ott himself. When I first got a job in Quality Assusrance, this was one of the books I consulted in my local college library. I soon found it was the best of the lot for its clear explanations, practical examples and sheer readability. When I came back into QA after working in another field, one of the first things I did was procure a copy of the book from a bookfinder - the 2nd hand copy I was delighted to discover also had Ott's signature! It is great to see an updated edition is now on sale and that Ellis Ott's name is not forgotten, for he (as far as I can find out about him) is one of the unsung pioneers of Statistical Process Control. Ott is not longer with us, but the co-authors have sensibly decided to update a classic, rather than starting from scratch. The examples in the older book are as relevant today as they are then. From what I can see, this book sticks to the philosophy of the earlier editions but has modernized its approach in some respects, especially in the notation of Experimental Design and in the use of Excel, which I also remommend as an easy-to-use PC tool. Highly recommended for practitioners of Statistical Process Control.

A Valuable Reference for Process Quality Control:
I recommend that this very well written text belong to every statistician who works in industry. Others such as mechanical, electrical, chemical, etc., engineers and scientists will also find this book to be a valuable reference. The book covers the breadth of useful statistical methods that industrial practitioners would likely encounter. Some topics such as implementing statistical process control, design of experiments with two or three factors, and troubleshooting with attributes and variables data are discussed extensively. Many real life examples from various industries are used throughout to illustrate the statistical concepts. All topics are well referenced enabling the reader to explore more thoroughly their areas of interest. The book also features a CD-ROM for the PC which contains datasets and solutions to practice exercises. An Excel add-in program is included for Analysis of Means \oANOM\c of attributes and variables data the results of which are presented graphically. The book is divided into three sections: Basics of Interpretation of Data, Statistical Process Control, and Troubleshooting and Process Improvement. The first section reviews many basic statistical concepts familiar to most statisticians. The second describes many facets of SPC some of which, such as Precontrol or Narrow-Limit Gauging in Process Control, the reader including myself may not be conversant, but will find useful in their own line of work. The last section describes what are probably underutilized but often very useful troubleshooting techniques. ANOM, for example, is a powerful way of analyzing data from industrial experiments with two or three factors resulting in graphics that can be used to clearly communicate conclusions to managers, to other engineers and scientists, and/or to operators on the shop floor. I really enjoyed reading this book and am finding it to be a valuable reference to which I refer again and again. Hank W. Altland Senior Project Engineer, Statistics Corning, Inc. August 26, 2000