Dynamic and steady-state performance analysis for multi-state repairable reconfigurable manufacturing systems with buffers

Yongjin Zhang, Ming Zhao, Yanjun Zhang, Ruilin Pan and Jing Cai

European Journal of Operational Research, 2020, vol. 283, issue 2, 491-510

Abstract: Reconfigurable manufacturing systems (RMSs) are considered the solution of choice when variable production capacity and functionality are required. A combinational approach, which integrates the steady-state probabilities of repairable reconfigurable machine tools (RMTs) and inventory-state probabilities of buffers through an improved universal generating function, is introduced in this study to assess the compound performance indicators (CPIs) of a repairable RMS. This paper contributes to the existing literature by considering the availability of buffers to calculate the CPIs of an RMS. In the proposed approach, the dynamic-state probability for each RMT is determined with a homogeneous continuous-time Markov model, and steady-state probability is obtained as the limit of the dynamic probability as time tends to infinity. In addition, a descriptive input-output information flow, which combines the conveying processes of the machined parts through buffers with the Poisson process, is proposed to determine the inventory-state probabilities of the buffers. Moreover, the explicit expressions of the CPI and expected performance rate (for the RMS and its constituent RMTs) are determined, and the validation procedure and technical details of the performance analysis for the Monte Carlo simulation are presented. Finally, a non-serial, repairable, multi-state RMS with multiple buffers that produces three types of engine cylinder heads is presented to validate the proposed approach. The simulation results verify the accuracy of the performance assessment of the RMS. It is useful for performance improvement in terms of machine reliability, resource utilisation efficiency, and decision-making concerning the configuration of RMS with buffers.

Keywords: Logistics; Reconfigurable manufacturing system; Dynamic and steady-state probability; Compound performance indicator; Universal generating function (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:283:y:2020:i:2:p:491-510

DOI: 10.1016/j.ejor.2019.11.013

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