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 | | Evolutionary Operation: A Statistical Method for Process Improvement (Wiley Classics Library) by George E. P. Box, Norman R. Draper ISBN-10: 9780471255512 ISBN-10: 0-471-25551-3 ISBN-13: 9780471255512 ISBN-13: 978-0-471-25551-2 Paperback 1998-03-09 Wiley-Interscience Find Lowest Price |
Editorials | ||
Product Description This book is about the philosophy and practice of Evolutionary Operation (called EVOP for short), a simple but powerful statistical tool with wide application in industry. Experience has long shown that statistical methods, sometimes quite sophisticated in character, can be of great value in improving the efficiency of laboratory and pilot-plant investigations made by specially trained chemists and engineers. What originally motivated the introduction of EVOP, however, was the idea that the widespread and daily use of simple statistical design and analysis during routine production by process operatives themselves could reap enormous additional rewards. | ||
Reviews | ||
statistical technique developed for manufacturing Evolutionary operation is a strategy for experimentation during production. It is a terrific method for continuous process improvement which is now popular in the new quality movement. Surprisingly, though very practical the approach never caught on when the book originally came out! Box and Draper are famous professors of statistics in the Statistics Department at the University of Wisconsin. Both are excellent writers and each has coauthored other very highly regarded texts. These techniques are worth considering by anyone involved in producing high quality manufacturing processes. This is the only text that covers the topic. | ||
reprint of a classic text from the late 1960s Evolutionary operation is a strategy for experimentation during production. It is a terrific method for continuous process improvement which is now popular in the new quality movement. Surprisingly, though very practical the approach never caught on when the book originally came out! Box and Draper are famous professors of statistics in the Statistics Department at the University of Wisconsin. Both are excellent writers and each has coauthored other very highly regarded texts. These techniques are worth considering by anyone involved in producing high quality manufacturing processes. This is the only text that covers the topic. | ||