Maintenance Optimization of Consecutive k outof n System with Multiobjective Birnbaum Importancebased Particle Swarm Optimization This paper focuses on the maintenance optimization problem of consecutivekoutofn systems which are maintained through exchanging the position of components and improving the reliability of components. At first, the multiobjective maintenance optimization model is constructed based on comprehensive consideration of the system reliability and maintenance cost. Then, the relationship between component reliability and maintenance cost is discussed and introduced into the Birnbaum importance to establish the idea of multiobjective Birnbaum importance (MOBI). It is clear that the maintenance strategy based on MOBI was more effective than the maintenance strategy based on traditional Birnbaum importance. Thirdly, the MOBIbased particle swarm optimization (MOBIPSO) method is proposed by taking the advantages of MOBI and particle swarm optimization. Finally, the MOBIPSO is applied to solve the problem of multiobjective maintenance optimization for consecutivekoutofn systems. The simulation results show that the optimization algorithm based on MOBI could make the system more reliable with lower maintenance cost after maintenance.

xe2x80x9cOptimal conditionbased maintenance with general repair and two dependent failure modesxe2x80x9d Abstract   This paper proposes a conditionbased maintenance (CBM) policy for a system subject to dependent soft and hard failures. When the deterioration exceeds a predetermined level, the system experiences a soft failure that can be rectified by corrective general repair or corrective replacement. Three possible actions, namely no maintenance, preventive general repair, and preventive replacement, are considered at each inspection epoch. The hard failure rate depending on both age and deterioration is described by a proportional hazards model with the covariate characterized by a gamma process. The hard failure can be corrected by minimal repair, general repair, or by replacement. Different from previous CBM policies, no thresholds are used to define maintenance actions. The objective is to determine the optimal maintenance policy that minimizes the longrun expected average cost per unit time. The optimization problem is formulated in the semiMarkov decision process (SMDP) framework and solved by the policy iteration algorithm. Two practical numerical examples are provided to illustrate the proposed policy. The comparison with other CBM policies shows an outstanding performance of the proposed policy, as well as the significance of minimal repair and general repair in CBM decision making.