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Titlebook: Disaggregation; Problems in manufact Larry P. Ritzman,Lee J. Krajewski,Lawrence D. Vitt Book 1979 Springer Science+Business Media Dordrecht

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书目名称Disaggregation
副标题Problems in manufact
编辑Larry P. Ritzman,Lee J. Krajewski,Lawrence D. Vitt
视频video
图书封面Titlebook: Disaggregation; Problems in manufact Larry P. Ritzman,Lee J. Krajewski,Lawrence D. Vitt Book 1979 Springer Science+Business Media Dordrecht
描述This volume is intended to expand the dialogue and interest among both practitioners and academicians in a problem area worthy of attention by all. The concept of disaggregation admits to our current inability to solve many types of interrelated hierarchical problems simultaneously. It offers instead a sequential, iterative process as a workable and necessary procedure. The papers in this volume are selected from those presented at a Disaggregation Conference held in March, 1977 at The Ohio State University. We heartily applaud all those who participated in the conference and particularly appreci­ ate the cooperation of those authors whose work is published in this collection. Part A contains four papers which define the various dimensions of disaggregation. The paper by Martin Starr, which was the text of his luncheon address at the conference, provides several interesting perspectives to the problem. Although disaggregation suggests tear­ ing apart, as Professor Starr illustrates with his butterfly example, it also suggests a putting together or a synthesis which recognizes interrelationships and dependencies. The next paper by Lee Kra­ jewski and Larry Ritzman offers a general m
出版日期Book 1979
关键词Manufacturing; algorithms; decision making; modeling; optimization; production; productivity; public policy
版次1
doihttps://doi.org/10.1007/978-94-015-7636-9
isbn_softcover978-94-015-7638-3
isbn_ebook978-94-015-7636-9
copyrightSpringer Science+Business Media Dordrecht 1979
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https://doi.org/10.1007/978-94-015-7636-9Manufacturing; algorithms; decision making; modeling; optimization; production; productivity; public policy
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Larry P. Ritzman,Lee J. Krajewski,Lawrence D. Vitt
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A Fuzzy Logic Inference System for Display Characterizationdy different configurations for the model and compare them with three state-of-the-art methods in terms of . visual error. This study is restricted to a single display and therefore we also point out what features of the learned model we think are more display dependent and might possibly change for a different display.
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