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dc.contributor.authorMishra, Rakesh J.-
dc.date.accessioned2014-11-24T10:07:25Z-
dc.date.available2014-11-24T10:07:25Z-
dc.date.issued2000-
dc.identifierM.Techen_US
dc.identifier.urihttp://hdl.handle.net/123456789/10672-
dc.guideJain, P. K.-
dc.description.abstractIn flexible manufacturing system, productivity is greatly affected by non-cutting time such as setup time, tool exchange time and index time. The physical constraints when minimizing this non-cutting time are determined by the relationships among machines, tools, fixtures and machining operations. There can be several features in each part and each feature can require several detailed machining operations. These operations can be unified as one operation sequence during process planning activity although they • may belong to the different parts, and the series of operations may be grouped into each set-up according to line balance. This study deals with such type of problem. In the present work the problems of determination of the optimal groups of machining operations and sequence of these operations in each groups from the view point of feasibility constraints are investigated. A method incorporating a combination of expert system and artificial neural network is proposed to perform grouping and sequencing of operations while minimizing the no-cutting time considering precedence, operation time, stage time and tool commonality as the considerations. A prototype CAPP system is also proposed which performs the tool selection, cost determination and the batch size determination. The advantage and effectiveness of the proposed approach is verified through an example of an actual manufacturing product and results have been compared with the earlier reported work on the same topic.en_US
dc.language.isoenen_US
dc.subjectMECHANICAL INDUSTRIAL ENGINEERINGen_US
dc.subjectPART GROUPINGen_US
dc.subjectOPERATION SEQUENCINGen_US
dc.subjectFMSen_US
dc.titlePART GROUPING AND OPERATION SEQUENCING IN FMS: AN INTEGRATED APPROACHen_US
dc.typeM.Tech Dessertationen_US
dc.accession.number248430en_US
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