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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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    1. Hichem Haddou Benderbal & Mohammed Dahane & Lyes Benyoucef, 2017. "Flexibility-based multi-objective approach for machines selection in reconfigurable manufacturing system (RMS) design under unavailability constraints," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 6033-6051, October.
    2. Kjølle, G.H. & Utne, I.B. & Gjerde, O., 2012. "Risk analysis of critical infrastructures emphasizing electricity supply and interdependencies," Reliability Engineering and System Safety, Elsevier, vol. 105(C), pages 80-89.
    3. Yu, Huan & Yang, Jun & Peng, Rui & Zhao, Yu, 2016. "Reliability evaluation of linear multi-state consecutively-connected systems constrained by m consecutive and n total gaps," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 35-43.
    4. Utne, I.B. & Hokstad, P. & Vatn, J., 2011. "A method for risk modeling of interdependencies in critical infrastructures," Reliability Engineering and System Safety, Elsevier, vol. 96(6), pages 671-678.
    5. Sun, Daniel (Jian) & Guan, Shituo, 2016. "Measuring vulnerability of urban metro network from line operation perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 348-359.
    6. 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.
    7. John Sherwood & Anthony Ditta & Becky Haney & Loren Haarsma & Michael Carbajales-Dale, 2017. "Resource Criticality in Modern Economies: Agent-Based Model Demonstrates Vulnerabilities from Technological Interdependence," Biophysical Economics and Resource Quality, Springer, vol. 2(3), pages 1-22, September.
    8. Jia Guo & Yuqi Han & Chuangxin Guo & Fengdan Lou & Yanbo Wang, 2017. "Modeling and Vulnerability Analysis of Cyber-Physical Power Systems Considering Network Topology and Power Flow Properties," Energies, MDPI, vol. 10(1), pages 1-21, January.
    9. Cagno, Enrico & De Ambroggi, Massimiliano & Grande, Ottavio & Trucco, Paolo, 2011. "Risk analysis of underground infrastructures in urban areas," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 139-148.
    10. Bye, Rolf J. & Aalberg, Asbjørn L., 2018. "Maritime navigation accidents and risk indicators: An exploratory statistical analysis using AIS data and accident reports," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 174-186.
    11. Burak Cavdaroglu & Erik Hammel & John Mitchell & Thomas Sharkey & William Wallace, 2013. "Integrating restoration and scheduling decisions for disrupted interdependent infrastructure systems," Annals of Operations Research, Springer, vol. 203(1), pages 279-294, March.
    12. Nicholas Santella & Laura J. Steinberg & Kyle Parks, 2009. "Decision Making for Extreme Events: Modeling Critical Infrastructure Interdependencies to Aid Mitigation and Response Planning," Review of Policy Research, Policy Studies Organization, vol. 26(4), pages 409-422, July.
    13. Zhang, Pengcheng & Peeta, Srinivas, 2014. "Dynamic and disequilibrium analysis of interdependent infrastructure systems," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 357-381.
    14. Zhuguang Lan & Ming Huang, 2018. "Safety assessment for seawall based on constrained maximum entropy projection pursuit model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(3), pages 1165-1178, April.
    15. Zio, E. & Ferrario, E., 2013. "A framework for the system-of-systems analysis of the risk for a safety-critical plant exposed to external events," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 114-125.
    16. Bompard, E. & Napoli, R. & Xue, F., 2009. "Assessment of information impacts in power system security against malicious attacks in a general framework," Reliability Engineering and System Safety, Elsevier, vol. 94(6), pages 1087-1094.
    17. Kaegi, M. & Mock, R. & Kröger, W., 2009. "Analyzing maintenance strategies by agent-based simulations: A feasibility study," Reliability Engineering and System Safety, Elsevier, vol. 94(9), pages 1416-1421.
    18. Yi Ge & Wen Dou & Haibo Zhang, 2017. "A New Framework for Understanding Urban Social Vulnerability from a Network Perspective," Sustainability, MDPI, vol. 9(10), pages 1-16, September.
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    1. Li, Yao & He, Yihai & Ai, Jun & Wang, Chengcheng & Han, Xiao & Liao, Ruoyu & Yang, Xiuzhen, 2022. "Functional health prognosis approach of multi-station manufacturing system considering coupling operational factors," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    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).

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