Minimisation of Non-periodic Preventive Maintenance Cost in Series-Parallel Systems

Te-Wei Lin; Chung-Ho Wang

doi:10.14429/dsj.61.61

Te-Wei Lin National Defense University, Taiwan
Chung-Ho Wang National Defense University, Taiwan

Keywords: Reliability, preventive maintenance, failure limit policy, importance measure

Abstract

A new method to optimise the non-periodic preventive maintenance model of a series-parallel system is proposed. A two-stage algorithm that incorporates the failure limit policy to determine maintenance components, maintenance times, and total maintenance cost is suggested. When the reliability of the system reaches a threshold value, preventive maintenance is performed. The first stage identifies the parallel subsystem required to be maintained, while the second stage determines the component required to be maintained in the parallel sub-system. A unit-cost life index (UCL) has been developed to evaluate the extent to which maintaining a component extends the life of a system for the parallel subsystem. Three simulated cases demonstrate the effectiveness and the practicality of the proposed method in optimising the non-periodic preventive maintenance model of a series-parallel system.

Defence Science Journal, 2011, 61(1), pp.44-50, DOI:http://dx.doi.org/10.14429/dsj.61.61

Author Biographies

Te-Wei Lin, National Defense University, Taiwan

Dr Chung-Ho Wang received his PhD from Dept of Industrial and Engineering and Management, National Chiao Tung University, Taiwan in 2001. He is a Professor of the Department of Power Vehicle and Systems Engineering at Chung Cheng Institute of Technology, National Defence University, Taiwan. His research areas include reliability theory, maintenance policies, and optimisation algorithm.

Chung-Ho Wang, National Defense University, Taiwan

Mr Te-wei Lin received his MS (weapon system engineering) from NDU in 2004. He is a PhD scholar at School of Defense Science, Chung Cheng Institute of Technology, National Defense University, Taiwan. His research areas include logistics engineering, reliability engineering and systems engineering.