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contributor authorYu Ding
contributor authorJianjun Shi
contributor authorDariusz Ceglarek
date accessioned2017-05-09T00:07:06Z
date available2017-05-09T00:07:06Z
date copyrightMarch, 2002
date issued2002
identifier issn0022-0434
identifier otherJDSMAA-26296#1_1.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/126532
description abstractVariation propagation in a multi-station manufacturing process (MMP) is described by the theory of “Stream of Variation.” Given that the measurements are obtained via certain sensor distribution scheme, the problem of whether the stream of variation of an MMP is diagnosable is of great interest to both academia and industry. We present a comprehensive study of the diagnosability of MMPs in this paper. It is based on the state space model and is parallel to the concept of observability in control theory. Analogous to the observability matrix and index, the diagnosability matrix and index are first defined and then derived for MMP systems. The result of diagnosability study is applied to the evaluation of sensor distribution strategy. It can also be used as the basis to develop an optimal sensor distribution algorithm. An example of a three-station assembly process with multi-fixture layouts is presented to illustrate the methodology.
publisherThe American Society of Mechanical Engineers (ASME)
titleDiagnosability Analysis of Multi-Station Manufacturing Processes
typeJournal Paper
journal volume124
journal issue1
journal titleJournal of Dynamic Systems, Measurement, and Control
identifier doi10.1115/1.1435645
journal fristpage1
journal lastpage13
identifier eissn1528-9028
keywordsMeasurement
keywordsSensors
keywordsManufacturing
keywordsJigs and fixtures AND Control theory
treeJournal of Dynamic Systems, Measurement, and Control:;2002:;volume( 124 ):;issue: 001
contenttypeFulltext


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