As those documents became more comprehensive they evolved into this textbook. In this practical introduction to DOE, guided by the capabilities of the common software packages, Paul Mathews presents the basic types and methods of designed experiments appropriate for engineers, scientists, quality engineers, and Six Sigma Black Belts and Master Black Belts. No part of this publication may be reproduced in any form, including an electronic retrieval system, without the prior written permission of ASQ. Design of Experiments with Minitab I still have and occasionally use Montgomery; Box, Hunter, and Hunter, Statistics for Experimenters; Hicks; and other DOE books, but as my own book has become more complete I find that I am using those books less and less often and then only for epxeriments.
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Mathews Paul G. Includes bibliographical references and index. ISBN hardcover, case binding : alk. Statistical hypothesis testing. Experimental design. M Not for resale. No part of this publication may be reproduced in any form, including an electronic retrieval system, without the prior written permission of ASQ. No part of this book may be reproduced in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher.
Publisher: William A. Attention Bookstores, Wholesalers, Schools and Corporations: ASQ Quality Press books, videotapes, audiotapes, and software are available at quantity discounts with bulk purchases for business, educational, or instructional use.
Box , Milwaukee, WI Visit our Web site at www. Design of experiments DOE is a methodology for studying any response that varies as a function of one or more independent variables or knobs.
By observing the response under a planned matrix of knob settings, a statistically valid mathematical model for the response can be determined.
Clearly, DOE is an essential tool for studying complex systems and it is the only rigorous replacement for the inferior but unfortunately still common practice of studying one variable at a time OVAT. However, GE knew from experience that this was a major weakness of most if not all of the entry-level engineers coming from any science or engineering program and still is today , and dealt with the prob- lem by offering a wonderful series of internal statistics courses.
To tell the truth, we spent most of our time in that class solving DOE problems with pocket calculators because there was lit- xiiixiiixiii tle software available at the time. Although to some degree the calculations distracted me from the bigger DOE picture, that course made the power and efficiency offered by DOE methods very apparent.
During my twelve years at GE Lighting I was involved in about one experiment per week. Many of the systems that we studied were so complex that there was no other possible way of doing the work. Although I learned the basic designs and methods of DOE at GE, I eventually real- ized that we had restricted ourselves to a relatively small subset of the available experi- ment designs.
This only became apparent to me after I started teaching and consulting on DOE to students and corporate clients who had much more diverse requirements.
I have to credit GE with giving me a strong foundation in DOE, but my students and clients get the credit for really opening my eyes to the true range of possibilities for designed experiments. The textbooks that I chose for those classes were Montgomery, Design and Analysis of Experiments and Hicks, Fundamental Concepts in the Design of Experiments, however, I felt that both of those books spent too much time describing the calculations that the software took care of for us and not enough time presenting the full capabilities offered by the software.
Since many students were still struggling to learn DOS while I was trying to teach them to use MINITAB, I supplemented their text- books with a series of documents that integrated material taken from the textbooks with instructions for using the software. As those documents became more comprehensive they evolved into this textbook.
I still have and occasionally use Montgomery; Box, Hunter, and Hunter, Statistics for Experimenters; Hicks; and other DOE books, but as my own book has become more complete I find that I am using those books less and less often and then only for reference. I purposely limited the scope of this book to the basic DOE designs and methods that I think are essential for any engineer or scientist to understand.
This book is limited to the study of quantitative responses using one-way and multi-way classifications, full xiv Preface and fractional factorial designs, and basic response-surface designs.
However, students who learn the material in this book and gain experience by running their own experiments will be well prepared to use those other books and address those other topics when it becomes necessary. Obviously this is an important topic. Even if you choose the perfect experiment to study a particular problem, that experiment will waste time and resources if it uses too many runs and 1.
Design of Experiments with Minitab
Design of Experiments with MINITAB
Design of Experiments with Minitab
Mathews Paul G. Design of Experiments with MINITAB