Efficient Artificial Immune Algorithm for Preventive- Maintenance-Planning For Multi State Systems
نویسندگان
چکیده
In this paper we use an artificial immune optimization algorithm in conjunction with the universal generating function (UGF) to solve the preventive maintenance (PM) problem for multistate series-parallel system. In this work, we consider the situation where system and its components have several ranges of performance levels. Such systems are called multi-state systems (MSS). To enhance system availability or (reliability), scheduled preventive maintenance actions are performed to equipments. These PM actions affect strongly the effective age of components and increase system reliability. The MSS measure is related to the ability of the system to satisfy the demand. The objective is to develop an algorithm to generate an optimal sequence of maintenance actions for providing a system working with the desired level of availability or (reliability) during its lifetime with minimal maintenance cost. To evaluate the MSS system availability, a fast method based on UGF is suggested. The immune algorithm (IA) approach is applied as an optimization technique and adapted to this PM optimization problem.
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