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contributor authorA. Khan
contributor authorD. Ceglarek
contributor authorJ. Shi
contributor authorJ. Ni
contributor authorT. C. Woo
date accessioned2017-05-09T00:00:22Z
date available2017-05-09T00:00:22Z
date copyrightFebruary, 1999
date issued1999
identifier issn1087-1357
identifier otherJMSEFK-27340#109_1.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/122537
description abstractFixture fault diagnosis is a critical component of currently evolving techniques aimed at manufacturing variation reduction. The impact of sensor location on the effectiveness of fault-type discrimination in such diagnostic procedures is significant. This paper proposes a methodology for achieving optimal fault-type discrimination through an optimized configuration of defined “sensor locales.” The optimization is presented in the context of autobody fixturing—a predominant cause of process variability in automobile assembly. The evaluation criterion for optimization is an improvement in the ability to provide consistency of best match, in a pattern recognition sense, of any fixture error to a classified, anticipated error set. The proposed analytical methodology is novel in addressing optimization by incorporating fixture design specifications in sensor locale planning—constituting a Design for Fault Detectability approach. Examples of the locale planning for a single fixture sensor layout and an application to an industrial fixture configuration are presented to illustrate the proposed methodology.
publisherThe American Society of Mechanical Engineers (ASME)
titleSensor Optimization for Fault Diagnosis in Single Fixture Systems: A Methodology
typeJournal Paper
journal volume121
journal issue1
journal titleJournal of Manufacturing Science and Engineering
identifier doi10.1115/1.2830562
journal fristpage109
journal lastpage117
identifier eissn1528-8935
keywordsSensors
keywordsJigs and fixtures
keywordsOptimization
keywordsFault diagnosis
keywordsDesign
keywordsManufacturing
keywordsErrors
keywordsFixturing
keywordsPattern recognition AND Automobiles
treeJournal of Manufacturing Science and Engineering:;1999:;volume( 121 ):;issue: 001
contenttypeFulltext


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