Powiadomienia systemowe
- Sesja wygasła!
- Sesja wygasła!
Identyfikatory
Warianty tytułu
Konferencja
15th Summer Safety & Reliability Seminars - SSARS 2021, 5-12 September 2021, Ciechocinek, Poland
Języki publikacji
Abstrakty
In this chapter the author presents a comprehensive model of a multi-component technical system aimed at simulating and optimizing its operation process. Among other things, the model postulates load-related dependencies between the system’s components and delayed repairs or replacements scheduled according to the components’ priorities, where delays result from limited maintenance personnel. During the last several decades researchers in the field of reliability theory constructed various maintenance models, more or less applicable to real systems. Many authors follow purely analytical approach which, due to restrictive assumptions adopted for the purpose of analytical tractability, results in limited applicability of the considered models. These assumptions include: mutually independent components, exponentially distributed time-to-failure and time-to-repair, repairs started immediately after failures or carried out in negligible time, etc. The model proposed here does not impose such limitations, because it is designed to use simulation rather than analytical methods for computing purposes. The following assumptions bring the model closer to reality in comparison with its counterparts from the literature: 1) components are mutually dependent, i.e. a component’s failure rate can depend of the states of some other components 2) after a repair a component can be “as good as new”, “as good as used” or “as good as old” (perfect, imperfect, or minimal repair) 3) if maintenance personnel is busy, newly failed components await repair in a priority queue, 4) the state of a component may be hidden and its failure can only be revealed by inspection. The chapter’s main result is a quite elaborate algorithm simulating the modeled system’s behavior over time. Examples are given how, based on the proposed model and the adopted maintenance policy, selected reliability-related parameters can be optimized by repeated simulation. Although computationally intensive, the simulation approach allows to find performance and reliability characteristics for systems whose complexity or way of functioning rule out the application of analytical methods.
Rocznik
Strony
293--304
Opis fizyczny
Bibliogr. 24 poz., rys., tab.
Twórcy
autor
- Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland
Bibliografia
- Alabdulkarim, A.A., Ball, P.D. & Tiwari, A. 2013. Applications of simulation in maintenance research. World Journal of Modelling and Simulation 9, 14-37.
- Barlow, R.E. & Proschan, F. 1975. Statistical Theory of Reliability and Life Testing: Probability Models. Holt, Rinehart and Winston, New York.
- Chouhan, R., Gaur, M. & Tripathi, R. 2013. A survey of preventive maintenance planning models, techniques and policies for an ageing and deteriorating production systems. HCTL Open International Journal of Technology Innovations and Research 3, 89-107.
- Dietrich, T., Krug, S. & Zimmermann, A. 2017. A discrete event simulation and evaluation framework for multi UAV system maintenance processes. 2017 IEEE International Systems Engineering Symposium (ISSE), 1-6.
- Dukhovny, A. & Marichal, J.-L. 2012. Reliability of systems with dependent components based on lattice polynomial description. Stochastic Models 28, 167-184.
- George-Williams, H. & Patelli, E. 2015. Monte-Carlo based reliability/availability analysis algorithm for efficient maintenance planning. Transactions, 23rd Conference on Structural Mechanics in Reactor Technology, Manchester, UK.
- Jardine, A.K.S. & Tsang, A.H.C. 2013. Maintenance, Replacement, and Reliability. CRC Press, Taylor & Francis Group.
- Lu, Z., Liu J., Dong. L & Liang, X. 2019. Maintenance process simulation based maintainability evaluation by using stochastic colored petri net. Applied Sciences 9(16), 3262.
- Lyubchenko,A.A., Kopytov E.Y., Bogdanov A.A. & Maystrenko V.A. 2020. Discrete-event simulation of operation and maintenance of telecommunication equipment using AnyLogic-based multi-state models. Journal of Physics: Conference Series 1441, 012046.
- Münsterberg, T. 2017. Simulation-based Evaluation of Operation and Maintenance Logistics Concepts for Offshore Wind Power Plants. Innovations for Maritime Logistics Volume 2. Fraunhofer Verlag.
- Nakagawa, T. 2008. Advanced Reliability Models and Maintenance Policies. Springer Series in Reliability Engineering, Springer, London.
- Nakagawa, T. 2014. Random Maintenance Policies. Springer Series in Reliability Engineering. Springer, London.
- Nakamura, S. & Qian, C.H. & Nakagawa, T. (Eds.). 2017. Reliability Modeling with Computer and Maintenance Applications. World Scientific, Singapore.
- O’Connor, P. & Kleyner, A. 2011. Practical Reliability Engineering. John Wiley & Sons.
- Panteleev, V.V., Kamaev, V.A. & Kizim, A.V. 2014.Developing a model of equipment maintenance and repair process at service repair company using agent-based approach. Procedia Technology 16, 1072-1079.
- Riane F., Roux O., Basile O. & Dehombreux P. 2009. Simulation based approaches for maintenance strategies optimization. Handbook of Maintenance Management and Engineering, 133-153.
- Rubinstein, R.Y. & Kroese, D.P. 2008. Simulation and the Monte Carlo Method, 2nd edition. John Wiley & Sons.
- Soltanali, H., Rohani, A., Tabasizadeh, M., Abbaspour-Fard, M.H. & Parida, A. 2019. Operational reliability evaluation-based maintenance planning for automotive production line. Quality Technology & Quantitative Management 17(2), 186-202.
- Sarkar, A., Panja, S.C. & Sarkar, B. 2011. Survey of maintenance policies for the last 50 years. International Journal of Software Engineering & Applications 2(3), 130-148.
- Vishnu, C.R. & Regikumar, V. 2016. Reliability based maintenance strategy selection in process plants: a case study. Procedia Technology 25, 1080-1087.
- Wang, H. 2002. A survey of maintenance policies of deteriorating systems. European Journal of Operations Research 139(3), 469-489.
- Yang, Q., Zhang, N. & Hong, Y. 2013. Reliability analysis of repairable systems with dependent component failures under partially perfect repair. IEEE Transactions on Reliability 62(2), 490-498.
- Zhang, T. & Horigome, M. 2001. Availability and reliability of system with dependent components and time-varying failure and repair rates. IEEE Transactions on Reliability 50(2), 151-158.
- Zhang, X. & Wilson, A. 2017. System reliability and component importance under dependence: a copula approach. Technometrics 59(2), 215-224.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d4609fcb-acd4-4746-9962-76c9be658758