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Degrading systems availability analysis: analytical semi-Markov approach
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Netaji Subhas Institute of Technology, Delhi, India
Delhi Technological University, Delhi, India
Management Development Institute, Gurugram, India
Publication date: 2021-03-31
Eksploatacja i Niezawodność – Maintenance and Reliability 2021;23(1):195-208
  • Semi-Markov Process (SMP) is used to model the probabilistic behavior of system.
  • SMP takes into account the dependencies and interactions between components of the system.
  • System model is developed which is solved using SMP to evaluate system availability.
  • The analysis results show that the maintenance policy: perfect repair with opportunistic maintenance is more efficient.
This paper deals with modeling and analysis of complex mechanical systems that deteriorate with age. As systems age, the questions on their availability and reliability start to surface. The system is believed to suffer from internal stochastic degradation mechanism that is described as a gradual and continuous process of performance deterioration. Therefore, it becomes difficult for maintenance engineer to model such system. Semi-Markov approach is proposed to analyze the degradation of complex mechanical systems. It involves constructing states corresponding to the system functionality status and constructing kernel matrix between the states. The construction of the transition matrix takes the failure rate and repair rate into account. Once the steady-state probability of the embedded Markov chain is computed, one can compute the steady-state solution and finally, the system availability. System models based on perfect repair without opportunistic and with opportunistic maintenance have been developed and the benefits of opportunistic maintenance are quantified in terms of increased system availability. The proposed methodology is demonstrated for a two-stage reciprocating air compressor with intercooler in between, system in series configuration.
Aju Kumar VN, Gandhi OP. Quantification of human error in maintenance using graph theory and matrix approach. Quality and Reliability Engineering International 2011; 27(8): 1145-72,
Barringer (2018) Weibull database.
Chen D, Trivedi KS. Optimization for condition-based maintenance with semi-Markov decision process. Reliability Engineering & System Safety 2005; 90(1): 25-29,
Cheng Z, Remenyte-Prescott R. Two probabilistic life-cycle maintenance models for the deteriorating pavement. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2018; 20 (3): 394-404,
Dong M. A novel approach to equipment health management based on auto-regressive hidden semi-Markov model (AR-HSMM). Science in China Series F: Information Sciences 2008; 51(9): 1291-304,
Foley AJ. Regime switching in currency markets and portfolio flows. Journal of Asset Management 2002; 2(4): 353-367,
Hu J, Zhang L. Risk based opportunistic maintenance model for complex mechanical systems. Expert Systems with Applications 2014; 41(6): 3105-3115,
Hu Z, Mahadevan S. Resilience assessment based on time-dependent system reliability analysis. Journal of Mechanical Design 2016; 138(11),
Jager P, Bertsche B. A new approach to gathering failure behavior information about mechanical components based on expert knowledge. In Annual Symposium Reliability and Maintainability, 2004-RAMS 2004 Jan 26 (pp. 90-95). IEEE.
Kharoufeh JP, Solo CJ, Ulukus MY. Semi-Markov models for degradation-based reliability. IEEE Transactions 2010; 42(8): 599-612,
Koutras VP, Platis AN. Semi-Markov availability modeling of a redundant system with partial and full rejuvenation actions. In2008 Third International Conference on Dependability of Computer Systems DepCoS-RELCOMEX 2008 Jun 26 (pp. 127-134),
Koutras VP, Platis AN. Semi-Markov performance modeling of a redundant system with partial, full and failed rejuvenation. International Journal of Critical Computer-Based Systems 2010; 1(1-3): 59-85,
Kulkarni VG. Modeling and analysis of stochastic systems. Crc Press; 2016 Nov 18.
Kumar G, Jain V, Gandhi OP. Availability analysis of repairable mechanical systems using analytical semi-Markov approach. Quality Engineering 2013; 25(2): 97-107,
Kumar G, Jain V, Gandhi OP. Reliability and availability analysis of mechanical systems using stochastic petri net modelling based on decomposition approach. International Journal of Reliability, Quality and Safety Engineering 2012; 19(01): 1250005,
Kumar S, Tewari PC, Kumar S, Gupta M. Availability optimization of CO-shift conversion system of a fertilizer plant using genetic algorithm technique. Bangladesh Journal of Scientific and Industrial Research 2010; 45(2): 133-140,
Laggoune R, Chateauneuf A, Aissani D. Opportunistic policy for optimal preventive maintenance of a multi-component system in continuous operating units. Computers & Chemical Engineering 2009; 33(9): 1499-1510,
Li H, Zhao Q. Reliability evaluation of fault tolerant control with a semi-Markov fault detection and isolation model. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 2006; 220(5): 329-338,
Lotovskyi E, Teixeira AP, Guedes Soares C. Availability analysis of an offshore oil and gas production system subjected to age-based preventive maintenance by Petri Nets. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22 (4): 627-637,
MATLAB, R2018a. (2018). Natick, Massachusetts, USA: Mathworks.
Moura MD, Droguett EL. A continuous-time semi-markov bayesian belief network model for availability measure estimation of fault tolerant systems. Pesquisa Operacional 2008; 28(2): 355-375,
Rajeevan AK, Shouri PV, Nair U. Markov modeling and reliability allocation in wind turbine for availability enhancement. Life Cycle Reliability and Safety Engineering 2018; 7(3): 147-157,
Samet S, Chelbi A, Hmida FB. Optimal availability of failure‐prone systems under imperfect maintenance actions. Journal of Quality in Maintenance Engineering 2010,
Samhouri MS. An intelligent opportunistic maintenance (OM) system: a genetic algorithm approach. In2009 IEEE Toronto International Conference Science and Technology for Humanity (TIC-STH) 2009 Sep 26 (pp. 60-65),
Shinde V, Biniwale D, Bharadwaj SK. Availability analysis for estimation of repair time of performance based logistics under operating condition. Journal of Reliability and Statistical Studies 2019; 12(1).
Vaidyanathan K, Trivedi KS. A comprehensive model for software rejuvenation. IEEE Transactions on Dependable and Secure Computing 2005; 2(2): 124-137,
Wang H. A survey of maintenance policies of deteriorating systems. European Journal of Operational Research 2002; 139(3): 469-489,
Wani MF, Gandhi OP. Development of maintainability index for mechanical systems. Reliability Engineering & System Safety 1999; 65(3): 259-270,
Wani MF, Gandhi OP. Failure analysis of mechanical systems based on function-cum-structure approach. International Journal of Performability Engineering 2008; 4(2): 141-152.
Welte TM. A rule-based approach for establishing states in a Markov process applied to maintenance modelling. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 2009; 223(1): 1-2,
Xie M, Kong H, Goh TN. Exponential approximation for maintained Weibull distributed component. Journal of Quality in Maintenance Engineering 2000,
Xie W, Hong Y, Trivedi K. Analysis of a two-level software rejuvenation policy. Reliability Engineering & System Safety 2005; 87(1): 13-22,
Zhou B, Yu J, Shao J, Trentesaux D. Bottleneck-based opportunistic maintenance model for series production systems. Journal of Quality in Maintenance Engineering 2015,
Zhu Y, Elsayed EA, Liao H, Chan LY. Availability optimization of systems subject to competing risk. European Journal of Operational Research 2010; 202(3): 781-788,
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