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

Author

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

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.

Suggested Citation

  • Zhang, Yongjin & Zhao, Ming & Zhang, Yanjun & Pan, Ruilin & Cai, Jing, 2020. "Dynamic and steady-state performance analysis for multi-state repairable reconfigurable manufacturing systems with buffers," European Journal of Operational Research, Elsevier, vol. 283(2), pages 491-510.
  • Handle: RePEc:eee:ejores:v:283:y:2020:i:2:p:491-510
    DOI: 10.1016/j.ejor.2019.11.013
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    1. Kamal Kumar Mittal & Pramod Kumar Jain & Dinesh Kumar, 2017. "Configuration selection in reconfigurable manufacturing system based on reconfigurability," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 27(3), pages 363-379.
    2. Liu, Jialu & Yang, Sheng & Wu, Aiguo & Hu, S. Jack, 2012. "Multi-state throughput analysis of a two-stage manufacturing system with parallel unreliable machines and a finite buffer," European Journal of Operational Research, Elsevier, vol. 219(2), pages 296-304.
    3. Lisnianski, Anatoly, 2007. "Extended block diagram method for a multi-state system reliability assessment," Reliability Engineering and System Safety, Elsevier, vol. 92(12), pages 1601-1607.
    4. Jafary, Bentolhoda & Fiondella, Lance, 2016. "A universal generating function-based multi-state system performance model subject to correlated failures," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 16-27.
    5. George-Williams, Hindolo & Patelli, Edoardo, 2017. "Efficient availability assessment of reconfigurable multi-state systems with interdependencies," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 431-444.
    6. Sihan Huang & Guoxin Wang & Yan Yan, 2019. "Delayed reconfigurable manufacturing system," International Journal of Production Research, Taylor & Francis Journals, vol. 57(8), pages 2372-2391, April.
    7. Fitouhi, Mohamed-Chahir & Nourelfath, Mustapha & Gershwin, Stanley B., 2017. "Performance evaluation of a two-machine line with a finite buffer and condition-based maintenance," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 61-72.
    8. Lutz, Christian M. & Roscoe Davis, K. & Sun, Minghe, 1998. "Determining buffer location and size in production lines using tabu search," European Journal of Operational Research, Elsevier, vol. 106(2-3), pages 301-316, April.
    9. Xia, Tangbin & Xi, Lifeng & Pan, Ershun & Ni, Jun, 2017. "Reconfiguration-oriented opportunistic maintenance policy for reconfigurable manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 87-98.
    10. Darvish, Maryam & Coelho, Leandro C., 2018. "Sequential versus integrated optimization: Production, location, inventory control, and distribution," European Journal of Operational Research, Elsevier, vol. 268(1), pages 203-214.
    11. Sagawa, Juliana Keiko & Nagano, Marcelo Seido & Speranza Neto, Mauro, 2017. "A closed-loop model of a multi-station and multi-product manufacturing system using bond graphs and hybrid controllers," European Journal of Operational Research, Elsevier, vol. 258(2), pages 677-691.
    12. Yuan, Xue-Ming & Liu, Liming, 2005. "Performance analysis of assembly systems with unreliable machines and finite buffers," European Journal of Operational Research, Elsevier, vol. 161(3), pages 854-871, March.
    13. Stanley B. Gershwin & Irvin C. Schick, 1983. "Modeling and Analysis of Three-Stage Transfer Lines with Unreliable Machines and Finite Buffers," Operations Research, INFORMS, vol. 31(2), pages 354-380, April.
    14. Ashutosh Singh & Shashank Gupta & Mohammad Asjad & Piyush Gupta, 2017. "Reconfigurable manufacturing systems: journey and the road ahead," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1849-1857, November.
    15. Ping-Chen Chang, 2019. "Reliability estimation for a stochastic production system with finite buffer storage by a simulation approach," Annals of Operations Research, Springer, vol. 277(1), pages 119-133, June.
    16. Svenja Lagershausen & Michael Manitz & Horst Tempelmeier, 2013. "Performance analysis of closed-loop assembly lines with general processing times and finite buffer spaces," IISE Transactions, Taylor & Francis Journals, vol. 45(5), pages 502-515.
    17. Sheng Yang & Cheng Wu & S. Hu, 2000. "Modeling and analysis of multi‐stage transfer lines with unreliable machines and finite buffers," Annals of Operations Research, Springer, vol. 93(1), pages 405-421, January.
    18. Gregory Levitin, 2005. "The Universal Generating Function in Reliability Analysis and Optimization," Springer Series in Reliability Engineering, Springer, number 978-1-84628-245-4, September.
    19. Shokraneh K. Moghaddam & Mahmoud Houshmand & Omid Fatahi Valilai, 2018. "Configuration design in scalable reconfigurable manufacturing systems (RMS); a case of single-product flow line (SPFL)," International Journal of Production Research, Taylor & Francis Journals, vol. 56(11), pages 3932-3954, June.
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    Cited by:

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    2. Jing Li & Guodong Wang & Haofei Zhou & Honggen Chen, 2023. "Redundancy allocation optimization for multi-state system with hierarchical performance requirements," Journal of Risk and Reliability, , vol. 237(6), pages 1031-1047, December.
    3. Zhang, Hanxiao & Sun, Muxia & Li, Yan-Fu, 2022. "Reliability–redundancy allocation problem in multi-state flow network: Minimal cut-based approximation scheme," Reliability Engineering and System Safety, Elsevier, vol. 225(C).

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