Reliability analysis and optimization of equal load-sharing k-out-of-n phased-mission systems

Jiakai, C.; Yan, H.; Wei, W.

Artykuł - szczegóły

Tytuł artykułu

Reliability analysis and optimization of equal load-sharing k-out-of-n phased-mission systems

Autorzy

Jiakai C. , Yan H. , Wei W.

Treść / Zawartość

Pełne teksty:

Pobierz

Identyfikatory

Warianty tytułu

Analiza niezawodności oraz optymalizacja systemów fazowych typu „k z n” o równym podziale obciążenia elementów składowych

Języki publikacji

Abstrakty

There are many studies on k-out-of-n systems, load-sharing systems (LSS) and phased-mission systems (PMS); however, little attention has been given to load-sharing k-out-of-n systems with phased-mission requirements. This paper considers equal loadsharing k-out-of-n phased-mission systems with identical components. A method is proposed for the phased-mission reliability analysis of the studied systems based on the applicable failure path (AFP). A modified universal generating function (UGF) is used in the AFP-searching algorithm because of its efficiency. The tampered failure rate load-sharing model for the exactly k-out-of-n: F system is introduced and integrated into the method. With the TFR model, the systems with arbitrary load-dependent component failure distributions can be analyzed. According to the time and space complexity analysis, this method is particularly suitable for systems with small k-values. Two applications of the method are introduced in this paper. 1) A genetic algorithm (GA) based on the method is presented to solve the operational scheduling problem of systems with independent submissions. Two theorems are provided to solve the problem under some special conditions. 2) The method is used to select the optimal number of components to make the system reliable and robust.

Istnieje wiele badań na temat systemów typu „k z n”, systemów z podziałem obciążenia (load-sharing systems, LSS) oraz systemów fazowych (tj. systemów o zadaniach okresowych) (phased-missionsystems, PMS); jak dotąd mało uwagi poświęcono jednak systemom typu „k z n” z podziałem obciążenia wymagającym realizacji różnych zadań w różnych przedziałach czasowych. Niniejszy artykuł omawia systemy fazowe typu „k z n” o równym podziale obciążenia przypadającego na identyczne elementy składowe. Zaproponowano metodę analizy niezawodności badanych systemów w poszczególnych fazach ich eksploatacji opartą na pojęciu właściwej ścieżki uszkodzeń (applicablefailurepath, AFP). W algorytmie wyszukującym AFP zastosowano zmodyfikowaną uniwersalną funkcję tworzącą (universal generating function, UGF), która cechuje się dużą wydajnością. Wprowadzono model manipulowanej intensywności uszkodzeń (tamperedfailurerate, TFR) elementów o równym podziale obciążenia dla systemu, w którym liczba uszkodzeń wynosi dokładnie k z n. Model ten włączono do proponowanej metody analizy niezawodności. Przy pomocy modelu TFR można analizować systemy o dowolnych rozkładach uszkodzeń części składowych, gdzie uszkodzenia są zależne od obciążenia. Zgodnie z analizą złożoności czasowej i przestrzennej, metoda ta jest szczególnie przydatna do modelowania układów o małych wartościach k. W pracy przedstawiono dwa zastosowania metody. 1) oparty o omawianą metodę algorytm genetyczny (GA) do rozwiązywania problemu harmonogramowania prac w systemach z niezależnymi podzadaniami. Sformułowano dwa twierdzenia pozwalające na rozwiązanie problemu w pewnych szczególnych warunkach. 2) Wybór optymalnej liczby elementów składowych pozwalającej na zachowanie niezawodności i odporności systemu.

Słowa kluczowe

Applicable Failure Path (AFP) genetic algorithm (GA) Phased-mission System (PMS) Tampered Failure Rate (TFR) Model Universal Generating Function (UGF)

właściwa ścieżka uszkodzeń AFP algorytm genetyczny GA system fazowy o zadaniach okresowych PMS Model manipulowanej intensywności uszkodzeń TFR Uniwersalna funkcja tworząca (UGF)

Wydawca

Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne

Czasopismo

Eksploatacja i Niezawodność

Rocznik

2015

Tom

Vol. 17, no. 2

Strony

250--259

Opis fizyczny

Bibliogr. 38 poz., rys., tab.

Twórcy

autor

Jiakai C.

cjkkaze@zju.edu.cn

College of Electrical Engineering Jiaoer 321, Yuquan Campus Zhejiang University Hangzhou, Zhejiang, China

autor

Yan H.

heyan@zju.edu.cn

College of Electrical Engineering Jiaoer 321, Yuquan Campus Zhejiang University Hangzhou, Zhejiang, China

autor

Wei W.

wwei@zju.edu.cn

College of Electrical Engineering Jiaoer 321, Yuquan Campus Zhejiang University Hangzhou, Zhejiang, China

Bibliografia

1. Amari S V, Bergman R. Reliability analysis of k-out-of-n load-sharing systems. Reliability and Maintainability Symposium, 2008. RAMS 2008. Annual. IEEE, 2008.
2. Amari S V, Krishna M B, Hoang P. Tampered failure rate load-sharing systems: status and perspectives. Handbook of Performability Engineering. Springer London. 2008; 291-308.
3. Amari S V, Misra K B, Pham H. Reliability analysis of tampered failure rate load-sharing k-out-of-n: G systems. Proc. 12th ISSAT Int. Conf. on Reliability and Quality in Design, Honolulu, Hawaii. 2006: 30-35.
4. Amari S V, Xing L. Reliability analysis of k-out-of-n systems with phased-mission requirements. International Journal of Performability Engineering, 2011; 7(6): 604 -609.
5. Back T. Evolutionary algorithms in theory and practice. Oxford University Press, New York.1996.
6. Bai D S, Yun W Y, Chung S W. Redundancy optimization of k-out-of-n systems with common-cause failures. Reliability, IEEE Transactions on, 1991; 40(1): 56-59, http://dx.doi.org/10.1109/24.75334.
7. Bhattacharyya G K, Soejoeti Z. A tampered failure rate model for step-stress accelerated life test. Communications in Statistics- Theory and Methods, 1989; 18(5): 1627-1643, http://dx.doi.org/10.1080/03610928908829990.
8. Birnbaum Z W, Esary J D, Saunders S C. Multi-component systems and structures and their reliability. Technometrics, 1961; 3(1): 55-77. http://dx.doi.org/10.1080/00401706.1961.1048992.
9. Cha J H, Yamamoto H, Yun W Y. Optimal Workload for a Multi-Tasking k-out-of-n: G Load Sharing System. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2006; 89(1): 288-296, http://dx.doi.org/10.1093/ietfec/e89-a.1.288
10. Cha J H, Yamamoto H, Yun W Y. Optimal Workload for a Multi-Tasking k-out-of-n: G Load Sharing System. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 2006; 89(1): 288-296, http://dx.doi.org/10.1093/ietfec/e89-a.1.288.
11. Dai J. A delay system approach to networked control systems with limited communication capacity. Journal of the Franklin Institute, 2010; 347(7): 1334-1352, http://dx.doi.org/10.1016/j.jfranklin.2010.06.00.
12. Destercke S, Sallak M.An extension of universal generating function in multi-state systems considering epistemic uncertainties. Reliability, IEEE Transactions on, 2013; 62(2): 504–514, http://dx.doi.org/10.1109/TR.2013.2259206.
13. Dhingra A K. Optimal apportionment of reliability and redundancy in series systems under multiple objectives. Reliability, IEEE Transactions on, 1992; 41(4): 576-582, http://dx.doi.org/10.1109/24.249589.
14. Goldberg D E. Genetic algorithms in search, optimization and machine learning. Addison Wesley, 1989.
15. Goyal P, Vin H M, Chen H. Start-time fair queueing: a scheduling algorithm for integrated services packet switching networks. ACM SIGCOMM Computer Communication Review. ACM, 1996, 26(4): 157-168.
16. Grigoriu M. Reliability analysis of dynamic Daniels systems with local load-sharing rule. Journal of engineering mechanics, 1990; 116(12): 2625-2642, http://dx.doi.org/10.1061/(ASCE)0733-9399(1990)116:12(2625).
17. Lad B K, Kulkarni M S, Misra K B. Optimal reliability design of a system. Handbook of Performability Engineering. Springer London. 2008; 499-519, http://dx.doi.org/10.1007/978-1-84800-131-2_32.
18. Levitin G. A universal generating function approach for the analysis of multi-state systems with dependent elements. Reliability Engineering & System Safety, 2004; 84(3): 285-292, http://dx.doi.org/10.1016/j.ress.2003.12.002.
19. Levitin G. The Universal Generating Function in Reliability Analysis and Optimization. Berlin, Germany: Springer-Verlag. 2005.
20. Levitin G, Xing L, Amari S V. Recursive algorithm for reliability evaluation of non-repairable phased mission systems with binary elements. Reliability, IEEE Transactions on, 2012; 61(2): 533-542, http://dx.doi.org/10.1109/TR.2012.2192060.
21. Levitin G, Xing L, Dai Y, 2013. Optimal Sequencing of Warm Standby Elements. Computers & Industrial Engineering, 65 (4): 570–576, http://dx.doi.org/10.1016/j.cie.2013.05.001.
22. Levitin G, Xing L, Dai Y. Cold-standby sequencing optimization considering mission cost. Reliability Engineering & System Safety, 2013; 118: 28–34, http://dx.doi.org/10.1016/j.ress.2013.04.010.
23. Liu H. Reliability of a load-sharing k-out-of-n: G system: non-iid components with arbitrary distributions. Reliability, IEEE Transactions on, 1998; 47(3): 279-284, http://dx.doi.org/10.1109/24.740502.
24. Mohammad R, Kalam A, Amari S V. Reliability evaluation of Phased-Mission Systems with load-sharing components. Reliability and Maintainability Symposium (RAMS), 2012 Proceedings-Annual. IEEE, 2012: 1-6.
25. Myers F A. k-out-of-n: G system reliability with imperfect fault coverage. Reliability, IEEE Transactions on, 2007; 56(3): 464- 473, http://dx.doi.org/10.1109/TR.2007.90322.
26. Pham H, Amari S, Misra R B. Reliability and MTTF prediction of k-out-of-n complex systems with components subjected to multiple stages of degradation. International journal of systems science, 1996; 27(10): 995-1000, http://dx.doi.org/10.1080/00207729608929304.
27. Rubinovitz J, Levitin G. Genetic algorithm for assembly line balancing. International Journal of Production Economics, 1995, 41(1): 343-354, http://dx.doi.org/10.1016/0925-5273(95)00059-3.
28. Syswerda G. A study of reproduction in generational and steady-state genetic algorithms. Foundations of genetic algorithms. Morgan Kaufmann. 1991.
29. Ushakov I A. A universal generating function. Soviet Journal of Computer and Systems Sciences, 1986, 24(5): 118-129.
30. Wang K S, Huang J J, Tsai Y T, Hsu F S. Study of loading policies for unequal strength shared-load system. Reliability Engineering & System Safety, 2002; 67(2): 119-128, http://dx.doi.org/10.1016/S0951-8320(99)00057-5.
31. Wang R, Fei H. Conditions for the coincidence of the TFR, TRV and CE models. Statistical papers, 2004; 45(3): 393- 412, http://dx.doi.org/10.1007/BF02777579.
32. Whitley L D. The GENITOR algorithm and selective pressure: why rank-based allocation of reproductive trials is best. ICGA. 1989, 89:116-123.
33. Wu X, Yan H, Li L. Numerical Method for Reliability Analysis of Phased-Mission System Using Markov Chains. Communications in Statistics-Theory and Method, 2012; 41(21): 3960-3973, http://dx.doi.org/10.1080/03610926.2012.697969.
34. Xing L, Amari S V. Reliability of phased-mission systems. Handbook of Performability Engineering. Springer London.2008; 349-368, http://dx.doi.org/10.1007/978-1-84800-131-2_2.
35. Xing L, Amari S V, Wang C. Reliability of k-out-of-n systems with phased-mission requirements and imperfect fault coverage. Reliability Engineering & System Safety, 2012; 103: 45-50, http://dx.doi.org/10.1016/j.ress.2012.03.018.
36. Xing L, Levitin G. BDD-based reliability evaluation of phased-mission systems with internal/external common-cause failures. Reliability Engineering & System Safety 2012;112: 145-153, http://dx.doi.org/10.1016/j.ress.2012.12.003.
37. Yun W Y, Kim G R, Yamamoto H. Economic design of a load-sharing consecutive k-out-of-n: F system. IIE Transactions, 2012; 44(1): 55-67, http://dx.doi.org/10.1080/0740817X.2011.590442.
38. Zang X, Sun H, Trivedi K S. A BDD-based algorithm for reliability analysis of phased-mission systems. Reliability, IEEE Transactions, 1999, 48(1): 50-60. http://dx.doi.org/10.1109/24.765927.

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-6a20cbe3-0ae9-4715-aef4-c1d83645c083