Modeling and performance analysis of a resource-sharing manufacturing system using stochastic Petri nets

Meng Chu Zhou, Frank DiCesare, Dianlong Guo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

25 Scopus citations

Abstract

The objectives of this work are to model a manufacturing system using top-down Petri net modeling approaches and mutual exclusion concepts; to construct stochastic Petri nets by considering the random failures of the machines, as well as such resources as robots and automated guided vehicle (AGV) systems, and by incorporating temporal variables to transitions and places; to derive the performance of the system using stochastic Petri net performance models for different cases; and to compare performance results. Performance analysis problems on both deadlock-free and deadlock-prone systems are addressed and a comparison between them is made. First the stochastic Petri net modeling process is discussed on the basis of top-down and bottom-up ideas. Then, system performance indices, such as throughput for a resource-sharing manufacturing system, are derived by using existing software packages such as SPNP. Finally, conclusions are drawn and future directions are discussed for Petri net evaluation of manufacturing systems.

Original languageEnglish (US)
Title of host publicationProc 5 IEEE Int Symp Intell Control 90
PublisherPubl by IEEE
Pages1005-1010
Number of pages6
ISBN (Print)0818621087
StatePublished - Dec 1 1990
EventProceedings of the 5th IEEE International Symposium on Intelligent Control 1990 - Philadelphia, PA, USA
Duration: Sep 5 1990Sep 7 1990

Publication series

NameProc 5 IEEE Int Symp Intell Control 90

Other

OtherProceedings of the 5th IEEE International Symposium on Intelligent Control 1990
CityPhiladelphia, PA, USA
Period9/5/909/7/90

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All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Zhou, M. C., DiCesare, F., & Guo, D. (1990). Modeling and performance analysis of a resource-sharing manufacturing system using stochastic Petri nets. In Proc 5 IEEE Int Symp Intell Control 90 (pp. 1005-1010). (Proc 5 IEEE Int Symp Intell Control 90). Publ by IEEE.