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Many authors have highlighted the importance of physical assets maintenance management in relation to resilience engineering, especially for systems operating under significant uncertainty. Thus, the authors presented a new approach to system maintenance based on resilience concept implementation. They introduced Maintenance Support Potentials (MSP) as a measure of an organization's maintenance support capacity. Moreover, based on the MSP definition, they developed a fuzzy-based organization's maintenance support potential level assessment method. The proposed approach takes into account two main MSP parameters – potential readiness level and process regency. It followed four main steps, including organization's MSP identification/evaluation, MSP weights assessment, Maintenance Support Capacity assessment, and final reasoning. A case study of a global manufacturer from the automotive industry is presented to illustrate the method's applicability. The authors also indicated further research directions to optimize the maintenance strategy based on Resilience-Based Maintenance concept.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
294--307
Opis fizyczny
Bibliogr. 52 poz., rys., tab.
Twórcy
autor
- WSB University, ul. Zygmunta Cieplaka 1c, 41-300 Dabrowa Gornicza, Poland
- Faculty of Mechanical Engineering, Department of Operation and Maintenance of Technical Systems, Wroclaw University of Science and Technology, ul. Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland
Bibliografia
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- 20. Jain P, Pistikopoulos EN, Mannan MS. Process resilience analysis based on data-driven maintenance optimization: Application to cooling tower operations. Computers and Chemical Engineering 2019; 121: 27-45, https://doi.org/10.1016/j.compchemeng.2018.10.019.
- 21. Jamshidi M, Titli A, Zadeh LA, Boverie S. (Eds.) Applications of Fuzzy Logic-towards High Machine Intelligence Quotient Systems. Environmental and Intelligent Manufacturing Systems Series, vol. 9, Prentice Hall, Upper Saddle River, NJ: 1997.
- 22. Klir G J, Yuan B. Fuzzy sets and fuzzy logic: theory and applications. Upper Saddle River, NJ: Prentice Hall, PTR: 1995.
- 23. Loska A. Remarks about modelling of maintenance processes with the use of scenario techniques. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2012; 14 (2): 92-98.
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- 25. Misra KB. Maintenance Engineering and Maintainability: An Introduction. In: Misra KB (eds): Handbook of Performability Engineering. Springer, London: 2008: 755-772, https://doi.org/10.1007/978-1-84800-131-2_46.
- 26. Moerman J-J, Braaksma J, van Dongen L. Resilient performance in maintenance operations: managing unexpected failures. In EurOMA 2017 conference proceedings. 24th International Annual EurOMA Conference 2017, Edinburgh, United Kingdom, 1/07/17, 1-10.
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- 31. PN-EN 13306:2010 Maintenance - Maintenance terminology. European Committee for Standardization, Bruxelles.
- 32. PN-EN 17007:2018-02 Maintenance process and associated indicators. European Committee for Standardization, Bruxelles.
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- 35. Ross T J. Fuzzy Logic with Engineering Applications. John Wiley and Sons: 2004.
- 36. Sun Ch-Ch. A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods. Expert Systems with Applications 2010; 37: 7745-7754, https://doi.org/10.1016/j.eswa.2010.04.066.
- 37. Talon A, Curt C. Selection of appropriate defuzzification methods: application to the assessment of dam performance. Expert Systems with Applications 2017; 70: 160-174, https://doi.org/10.1016/j.eswa.2016.09.004.
- 38. Tripathy DP, Ala CK. Risk assessment in underground coal mines using fuzzy logic in the presence of uncertainty. Journal of The Institution of Engineers (India): Series D 2018; 99(1): 157-163, https://doi.org/10.1007/s40033-018-0154-7.
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- 40. Verma S, Chaudhri S. Integration of fuzzy reasoning approach (FRA) and fuzzy analytic hierarchy process (FAHP) for risk assessment in mining industry. Journal of Industrial Engineering and Management 2014; 7: 1347-1367, https://doi.org/10.3926/jiem.948.
- 41. Wang H, Duan F, Ma J. Reliability analysis of complex uncertainty multi-state system based on Bayesian network. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2019; 21 (3): 419-429, https://doi.org/10.17531/ein.2019.3.8.
- 42. Werbińska-Wojciechowska S. Technical system maintenance. Delay-Time-Based Modelling. Springer Nature Switzerland AG: 2019, https://doi.org/10.1007/978-3-030-10788-8.
- 43. Yan S, MA B, Wang X, Chen J, Zheng C. Maintenance policy for oil-lubricated systems with oil analysis data. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (3): 455-464, https://doi.org/10.17531/ein.2020.3.8.
- 44. Yazdi M, Nikfar F, Nasrabadi M. Failure probability analysis by employing fuzzy fault tree analysis. International Journal of System Assurance Engineering and Management 2017; 8: 1177-1193, https://doi.org/10.1007/s13198-017-0583-y.
- 45. Yen J, Langari R. Fuzzy Logic: Intelligence, Control and Information. Prentice Hall, Berlin: 1998.
- 46. You L, Zhang J, Li Q, Ye N. Structural reliability analysis based on fuzzy random uncertainty. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2019; 21 (4): 599-609, https://doi.org/10.17531/ein.2019.4.9.
- 47. Zadeh L A. Toward a generalized theory of uncertainty (GTU) - an outline. Information Sciences 2005; 172: 1-40, https://doi.org/10.1016/j.ins.2005.01.017.
- 48. Zadeh L A. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Systems 1978; 1: 3-28, https://doi.org/10.1016/S0165-0114(99)80004-9.
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- 51. Zheng J H. A fuzzy TOPSIS approach based to evaluate the transportation mode selection: an experience in a suburban university. Advances in Transportation Studies, Special Issue 2015; 1: 23-34, https://doi.org/10.4399/978885488881403.
- 52. Zhiyong G, Jiwu L, Rongxi W. Prognostics uncertainty reduction by right-time prediction of remaining useful life based on hidden Markov model and proportional hazard model. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2021; 23 (1): 154-164, https://doi.org/10.17531/ein.2021.1.16.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-db132737-2f94-474d-bf99-fb163f904fa6