Modelling reconfigurable manufacturing systems with coloured timed Petri nets

Reconfigurable manufacturing systems (RMSs) have been acknowledged as a promising means of providing manufacturing companies with the required production capacities and capabilities. This is accomplished through reconfiguring system elements over time for a diverse set of individualised products oft...

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Bibliographic Details
Main Authors: ZHANG, Lianfeng, RODRIGUES, Brian
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2009
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Online Access:https://ink.library.smu.edu.sg/lkcsb_research/1823
https://ink.library.smu.edu.sg/context/lkcsb_research/article/2822/viewcontent/ModellingReconfigManuSysPN_2009_pp.pdf
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Institution: Singapore Management University
Language: English
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Summary:Reconfigurable manufacturing systems (RMSs) have been acknowledged as a promising means of providing manufacturing companies with the required production capacities and capabilities. This is accomplished through reconfiguring system elements over time for a diverse set of individualised products often required in small quantities and with short delivery lead times. Recognising the importance of dynamic modelling and visualisation in decision-making support in RMSs and the limitations of current research, we propose in this paper to model RMSs with Petri net (PN) techniques with focus on the process of reconfiguring system elements while considering constraints and system performance. In view of the modelling challenges, including variety handling, production variation accommodation, machine selection, and constraint satisfaction, we develop a new formalism of coloured timed PNs. In conjunction with coloured tokens and timing in coloured and timed PNs, we also define a reconfiguration mechanism to meet modelling challenges. An application case from an electronics company producing mobile phone vibration motors is presented. Also reported are system analysis and application results, which show how the proposed formalism can be used in the reconfiguration decision making process.