Reliability analysis of multi-state repairable system with dynamic transition probabilities
Tóm tắt
Inadequate maintenance decisions lead to incremental overall costs. In order to minimize costs in maintenance of the multi-state repairable system, we model a preventive maintenance (PM) scheme of the multistate repairable system using non-Markov process. The periodically decreasing reliability model of the non-Markov dynamic system with dynamic transition probabilities is established to satisfy the probability change. The diesel engine system is taken as an example to illustrate the model. The reliability of the diesel engine is analyzed and its PM scheme is worked out. RENO software is used to simulate the diesel engine system. The maintenance cost of components and the optimal PM interval data of the system are obtained by using the minimal average cost as the objective function. The adaptability of PM is judged, and the optimal PM scheme is presented.
Tài liệu tham khảo
GU Y K, LI J. Multi-state system reliability: A new and systematic review [J]. Procedia Engineering, 2012, 29: 531–536.
BOBADILLA R G. Modeling risk of a multi-state repairable component [D]. Edmonton, Canada: Department of Mechanical Engineering, University of Alberta, 2009.
PINTELON L M, GELDERS L F. Maintenance management decision making [J]. European Journal of Operational Research, 1992, 58(3): 301–317.
PANDEY M, ZUO M J, MOGHADDASS R, et al. Selective maintenance for binary systems under imperfect repair [J]. Reliability Engineering and System Safety, 2013, 113(1): 42–51.
SHEU D D, KUO J Y. A model for preventive maintenance operations and forecasting [J]. Journal of Intelligent Manufacturing, 2006, 17(4): 441–451.
LIU Y, HUANG H Z. Optimal selective maintenance strategy for multi-state systems under imperfect maintenance [J]. IEEE Transactions on Reliability, 2010, 59(2): 356–367.
CAI J, ZUO H F, WANG H W. A study on preventive maintenance optimization model for multi-unit system [J]. Systems Engineering Theory and Practice, 2007, 27(2): 133–138 (in Chinese).