Evaluation of the logistic model of the reconfigurable manufacturing system based on generalised stochastic Petri nets

• Published in: International journal of production research Vol. 50; no. 22; pp. 6249 - 6258
• Main Authors: Li, G.Q., Mitrouchev, P., Wang, Y., Brissaud, D., Lu, L.X.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis Group 15.11.2012; Taylor & Francis; Taylor & Francis LLC
• Subjects: Applied sciences; Exact sciences and technology; generalised stochastic Petri nets; Inventory control, production control. Distribution; Logistics; logistics model; Manufacturing; Manufacturing cells; manufacturing systems; Markov analysis; Markov chain; Mathematical models; Modular; Modules; Operational research and scientific management; Operational research. Management science; Petri nets; Production capacity; Productivity; Stochastic models; Stochasticity; Studies; Productivity; Production system; Bottleneck; Service process; logistics model; Markov model; Modeling; Markov chain; generalised stochastic Petri nets; Flexible manufacturing system; Cellular manufacturing; manufacturing systems; Production capacity; Reconfigurable architectures; Logistics; Production process; Petri net
• ISSN: 0020-7543; 1366-588X
• DOI: 10.1080/00207543.2011.616235

To reveal the influence on system performance by the logistic model of reconfigurable manufacturing system (RMS), the generalised stochastic Petri nets (GSPN) modular modelling approach is presented in this paper. It is based upon the characteristics of a bottleneck service. According to this approach, the bottleneck service in the production process is found first. By corresponding different resources in the service to different modules of the GSPN, the module is reconfigured. The analysis of the model using the Markov chain is hereby presented, as is the average utilisation factor of RMS. Following this, the production capacity of different products and the average productivity of reconfigurable manufacturing cells (RMCs) are discussed.