Performance evaluation of manufacturing systems using stochastic activity networks

Persistent Link:
http://hdl.handle.net/10150/278068
Title:
Performance evaluation of manufacturing systems using stochastic activity networks
Author:
Shah, Hemal Vinodchandra, 1967-
Issue Date:
1991
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
In this thesis, Stochastic Activity Networks (SANs), which are an extension to the Petri Nets, are used for performance evaluation of manufacturing systems. Using our formalism, a manufacturing system is hierarchically represented in three different layers: the manufacturing flow layer, the control layer and the network layer. SAN models are constructed for each of these layers. To simplify the understanding of the manufacturing flow, a new graphical representation, the Manufacturing Flow Network (MFN) has been developed. Conversion of MFN into SAN models simplifies the modeling of manufacturing flow layer. When MFN at the product level is very complex, a decomposition technique is applied to reduce complexity of the model under specific conditions. The accuracy of this technique is shown for specific conditions. Finally, a performance evaluation of a sample manufacturing system is shown, using the simulation for solution of the model. Performance variables of interest such as machine utilization, machine availability and operation queue length are discussed.
Type:
text; Thesis-Reproduction (electronic)
Keywords:
Engineering, Electronics and Electrical.; Engineering, Industrial.; Computer Science.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College
Degree Grantor:
University of Arizona
Advisor:
Sanders, William H.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titlePerformance evaluation of manufacturing systems using stochastic activity networksen_US
dc.creatorShah, Hemal Vinodchandra, 1967-en_US
dc.contributor.authorShah, Hemal Vinodchandra, 1967-en_US
dc.date.issued1991en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractIn this thesis, Stochastic Activity Networks (SANs), which are an extension to the Petri Nets, are used for performance evaluation of manufacturing systems. Using our formalism, a manufacturing system is hierarchically represented in three different layers: the manufacturing flow layer, the control layer and the network layer. SAN models are constructed for each of these layers. To simplify the understanding of the manufacturing flow, a new graphical representation, the Manufacturing Flow Network (MFN) has been developed. Conversion of MFN into SAN models simplifies the modeling of manufacturing flow layer. When MFN at the product level is very complex, a decomposition technique is applied to reduce complexity of the model under specific conditions. The accuracy of this technique is shown for specific conditions. Finally, a performance evaluation of a sample manufacturing system is shown, using the simulation for solution of the model. Performance variables of interest such as machine utilization, machine availability and operation queue length are discussed.en_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
dc.subjectEngineering, Electronics and Electrical.en_US
dc.subjectEngineering, Industrial.en_US
dc.subjectComputer Science.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorSanders, William H.en_US
dc.identifier.proquest1346746en_US
dc.identifier.bibrecord.b27280512en_US
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