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Reliability evaluation for multi-state repairable systems with hybridization the markov stochastic process and the universal generating function

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
PL
Określenie niezawodności w wielostanowych naprawialnym systemie z hybrydyzacją procesu Markova i użyciem funkcji UGF
Języki publikacji
EN
Abstrakty
EN
Multistate reliability models are generally complicated and the state space has a large number of states. Evaluating the performance distribution of complex series parallel to the repairable multi-state system with dependent linear components. They are much more complex and present major difficulties in defining the system and the performance of the MSS multistate reliability assessment system. A new approach is introduced to extend the classical theory of reliability based on the binary hypothesis to the repairable multi-state system (MSS). Generally, some of the stochastic processes of traditional methods did not provide an assessment of the reliability of the MSS system due to the enormous states of the system. This article is based on the hybridization of the Markov stochastic process and the universal generation function technology (UGF) which deals with the most sophisticated and realistic models ranging from perfect operation to complete failure in which components and systems can take many states. We consider the case where the performance and probability distributions of certain components depend on the linear of another component or group of components.
PL
Zaprezentowano nowa metodę rozszerzająca klasyczną teorię niezawodności bazującą na hipotezie naprawialnych systemów wielostanowych MSS. Artykuł bazuje na hybrydyzacji stochastycznego procesu Markova i technologii uniwersalnej funkcji UGF. Rozważono przypadek kiedy gęstość prawdopodobieństwa pewnych składowych zależy liniowo od innych składowych.
Rocznik
Strony
109--114
Opis fizyczny
Bibliogr. 26 poz., rys., tab.
Twórcy
  • University of Moulay Tahar, Saida
  • University of Sidi-Bel-Abbes. Algeria
  • University of Moulay Tahar, Saida
Bibliografia
  • [1] I.A. Ushakov, G. Levitin and A. Lisnianski. Multi-state system reliability: from theory to practice. Proc. of 3 Int. Conf. on mathematical methods in reliability, MMR 2002, Trondheim, Norway, pp. 635-638.
  • [2] G. Levitin and A. Lisnianski, A new approach to solving problems of multi-state system reliability optimization. Quality and Reliability Engineering International, 2001, vol. 47, No. 2, pp. 93-104.
  • [3] Hui.Xiao, Rui.Peng, *Optimal allocation and maintenance of multi-state elements in series–parallel systems with common bus performance sharing , Computers & Industrial Engineering, June 2014, vol 72, pp 143-151.
  • [4] B. Murchland. Fundamental concepts and relations for reliability analysis of multi-state systems. Reliability and Fault Tree Analysis, ed. R. Barlow, J. Fussell, N. Singpurwalla. SIAM, Philadelphia. 1975.
  • [5] I.A. Ushakov. Optimal standby problems and a universal generating function. Sov. J. Computing System Science, Vol. 25, N 4, 1987, pp 79-82.
  • [6] I.A. Ushakov. Universal generating function. Sov. J. Computing System Science, Vol. 24, N 5, 1986, pp 118-129.
  • [7] Wang, L. Y. and Cui, L R. Aggregated semi-Markov repairable systems with history-dependent up and down states. Mathematical and Computer Modelling, 2011, vol 53, pp 883-895.
  • [8] Vidhya G Nair, M. Manoharan. Dynamic Multi State System Reliability Analysis of Power Generating Systems using Lztransform, ProbStat Forum, July 2018, vol 11, pp 81-90.
  • [9] Arash. Zaretalab, Vahid. Hajipour, Madjid. Tavana, Redundancy Allocation Problem with Multi-State Component Systems and Reliable Supplier Selection, Reliability Engineering, January 2020, vol 193, pp 106-129.
  • [10] S. P. Sharma and Yashi Vishwakarma, Application of Markov Process in Performance Analysis of Feeding System of Sugar Industry, Hindawi , Journal of Industrial Mathematics, Volume 2014.
  • [11] Liying. Wang, Xujie. Jia and Jie. Zhang, Reliability Evaluation for Multi-State MarkovRepairable Systems with Redundant Dependencies, Quality Technology & Quantitative Management, 2013, Vol. 10, No. 3, pp. 277-289.
  • [12] Jin-Zhang Jia, Zhuang Li,Peng Jia, and Zhi-guo Yang, Reliability Analysis of Common Cause Failure Multistate System Based on CUGF, Hindawi Mathematical Problems in Engineering, 22 May 2020, Volume14.
  • [13] Essa Abrahim, Abdulgader. Saleem, Thien-My Dao, Zhaoheng Liu, Multi-objective optimization of multi-state reliability system using hybrid metaheuristic genetic algorithm and fuzzy function for redundancy allocation, American Journal of Engineering Research (AJER), 2017, Volume-6, Issue-10, pp-98-107.
  • [14] H. Yu, C. Chu, Châtelet, F. Yalaoui, Reliability optimization of a redundant system with failure dependencies, Reliab. Eng. Syst. Safety, vol 92, 2007, pp 1627–1634.
  • [15] A. Lisnianski and Y. Ding, Redundancy analysis for repairable multistates system by using combined stochastic processes methods and universal generating function technique, Reliability Engineering and System Safety, 2009, vol.94, pp. 1788-1795.
  • [16] Shahrzad Faghih-Roohi a,n, Min Xie a,b, Kien Ming Ng a, Richard C.M. Yam, Dynamic availability assessment and optimal component design of multi-state weighted k-out-of-n systems, Reliability Engineering & System Safety, March 2014, vol 123, pp 57-62.
  • [17] Fricks, R. M. and Trivedi, K. S. Modeling failure dependencies in reliability analysis using stochastic petri-nets, Proceedings of European Simulation Multiconference, 1997.
  • [18] Mo. Y, Xing. L, Zhong. F, Zhang, Z, * Reliability evaluation of network systems with dependent propagated failures using decision diagrams, IEEE Transactions on Dependable and Secure Computing, 2015, vol 13(6), pp 672-683.
  • [19] Gregory. Levitin, A universal generating function approach for the analysis of multi-state systems with dependent elements, Elsevier 2004 Reliability Engineering and System Safety 84, 2004, pp 285–292.
  • [20] Haiyang Yu, Chengbin Chu, Éric Châtelet, Availability optimization of a redundant system through dependency modeling, Appl. Math. Modell. 2014.
  • [21] Liying .Wang, Xujie. Jia, Jie.Zhang. Reliability Evaluation for Multi-State Markov Repairable Systems with Redundant Dependencies, Quality Technology & Quantitative Management, 2013 ,Vol. 10, No. 3, pp. 277-289.
  • [22] Liying .Wang, Qing. Yang, Yuran. Tian, Reliability Analysis of 6-Component Star Markov Repairable System with Spatial Dependence, Hindawi Mathematical Problems in Engineering, February 2017, vol, pp 7.
  • [23] M. Amara, R. Meziane, A. Zeblah, Cost Optimization for Series-Parallel Petroleum Transportation Pape-Lines under Reliability Constraints, Journal of Engineering Research and Applications, January 2014, Vol. 4, pp.302-310.
  • [24] Meziane. Rachid, Boufala. Sedik, Hamzi. Amar, Amara. Mohamed, Hybrid Wind Gas Reliability Optimization using Gravitational Search Algorithm under Performance and Cost Constraints, Australian Journal of Basic and Applied Sciences, 8(15) September 2014, vol 8(15) , pp 127-136.
  • [25] Abdelkrim.Chaker,Abdelkader.Benaissa,Aabdelkader.Zeblah, Optimal Allocation of the Electrical Structure Design using the Bats Approach, PRZEGLĄD ELEKTROTECHNICZNY, 2020, vo 06, pp 98-102.
  • [26] Y.F. Li ,.R. Peng, Availability modeling and optimization of dynamic multi-state series–parallel systems with random reconfiguration, Reliability Engineering & System Safety, July 2014, vol 127, pp 47-57.
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-6b68efaa-d2e6-4e41-80d3-edb0929eba30
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