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Structural-vulnerability assessment of reconfigurable manufacturing system based on universal generating function

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  • Gao, Guibing
  • Wang, Junshen
  • Yue, Wenhui
  • Ou, Wenchu

Abstract

Reconfigurable manufacturing systems (RMSs) must be accurately designed in enterprises as it is subjected to many types of disturbances. Modeling the direct impact of each type of disturbance on RMSs and analyzing their structural-level vulnerabilities is significant for operating and optimizing RMSs. In this study, the structural vulnerability of RMSs was evaluated based on the principle of entropy and a Markov model. The proposed approach includes (a) a multistate Markov transfer equation of the manufacturing unit, (b) a method for analyzing the state and calculating the brittleness entropy of manufacturing units, (c) a method for identifying the impact of the status and capacity of a buffer on the structural vulnerability, (d) an efficient state simplification technique for RMSs based on the universal generating function (UGF) method, and (e) a quantitative assessment of the structural vulnerability. Moreover, the proposed approach was used to evaluate the structural vulnerability based on pertinent-vulnerability analyses with a cartoon box production line as an example. The results show that (a) the units connected in series are more vulnerable and that the state of the unit affects the system vulnerability, (b) the buffers reduce the system vulnerability, and (c) the UGF method significantly improves the efficiency of the vulnerability evaluation.

Suggested Citation

  • Gao, Guibing & Wang, Junshen & Yue, Wenhui & Ou, Wenchu, 2020. "Structural-vulnerability assessment of reconfigurable manufacturing system based on universal generating function," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    • Handle: RePEc:eee:reensy:v:203:y:2020:i:c:s0951832020306025
    DOI: 10.1016/j.ress.2020.107101
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    2. Ma, Ye & Chi, Yuanying & Wu, Di & Peng, Rui & Wu, Shaomin, 2021. "Reliability of integrated electricity and gas supply system with performance substitution and sharing mechanisms," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    3. Li, Jingkui & Lu, Yuze & Liu, Xiaona & Jiang, Xiuhong, 2023. "Reliability analysis of cold-standby phased-mission system based on GO-FLOW methodology and the universal generating function," Reliability Engineering and System Safety, Elsevier, vol. 233(C).
    4. Zhang, Tian & Homri, Lazhar & Dantan, Jean-Yves & Siadat, Ali, 2023. "Models for reliability assessment of reconfigurable manufacturing system regarding configuration orders," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    5. GAO, Guibing & ZHOU, Dengming & TANG, Hao & HU, Xin, 2021. "An Intelligent Health diagnosis and Maintenance Decision-making approach in Smart Manufacturing," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    6. Xia, Weifu & Wang, Yanhui & Hao, Yucheng & He, Zhichao & Yan, Kai & Zhao, Fan, 2024. "Reliability analysis for complex electromechanical multi-state systems utilizing universal generating function techniques," Reliability Engineering and System Safety, Elsevier, vol. 244(C).

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