Performance evaluation of manufacturing systems using stochastic activity networks
| dc.contributor.advisor | Sanders, William H. | en_US |
| dc.contributor.author | Shah, Hemal Vinodchandra, 1967- | |
| dc.creator | Shah, Hemal Vinodchandra, 1967- | en_US |
| dc.date.accessioned | 2013-04-03T13:11:43Z | |
| dc.date.available | 2013-04-03T13:11:43Z | |
| dc.date.issued | 1991 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10150/278068 | |
| dc.description.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. | |
| dc.language.iso | en_US | en_US |
| dc.publisher | The University of Arizona. | en_US |
| dc.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. | en_US |
| dc.subject | Engineering, Electronics and Electrical. | en_US |
| dc.subject | Engineering, Industrial. | en_US |
| dc.subject | Computer Science. | en_US |
| dc.title | Performance evaluation of manufacturing systems using stochastic activity networks | en_US |
| dc.type | text | en_US |
| dc.type | Thesis-Reproduction (electronic) | en_US |
| thesis.degree.grantor | University of Arizona | en_US |
| thesis.degree.level | masters | en_US |
| dc.identifier.proquest | 1346746 | en_US |
| thesis.degree.discipline | Graduate College | en_US |
| thesis.degree.name | M.S. | en_US |
| dc.identifier.bibrecord | .b27280512 | en_US |
| refterms.dateFOA | 2018-06-28T23:37:15Z | |
| html.description.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. |
