Zhisheng Zhang

Maintenance optimisation of a multi-state series–parallel system considering economic dependence and state-dependent inspection intervals

Abstract This paper presents a maintenance optimisation method for a multi-state series–parallel system considering economic dependence and state-dependent inspection intervals. The objective function considered in the paper is the average revenue per unit time calculated based on the semi-regenerative theory and the universal generating function (UGF). A new algorithm using the stochastic ordering is also developed in this paper to reduce the search space of maintenance strategies and to enhance the efficiency of optimisation algorithms. A numerical simulation is presented in the study to evaluate the efficiency of the proposed maintenance strategy and optimisation algorithms. The simulation result reveals that maintenance strategies with opportunistic maintenance and state-dependent inspection intervals are more cost-effective when the influence of economic dependence and inspection cost is significant. The study further demonstrates that the optimisation algorithm proposed in this paper has higher computational efficiency than the commonly employed heuristic algorithms.

Maintenance optimization for a system with an implemented interval of replacement activities

Most research on maintenance optimization regarded that a replacement activity is performed as soon as a planned time reaches, some other considered a time delay on replacement schedule when one job is completed or a failure comes. However, there is no existing research taking into account the influence of changes of the replacement schedule and catastrophic failures of a system on the replacement activity. In this paper, Failures of the system are divided into minor and catastrophic ones, and the replacement activity is performed either at the time when a catastrophic failure happens or in the implemented interval of the replacement activity randomly, whichever comes first. The objective of this paper is to find a constraint on the implemented interval length which is determined by engineers and an optimal implemented range of replacement activities for minimize the mean maintenance cost.

An efficient maintenance optimisation method for series-parallel systems using stochastic ordering and revenue difference boundaries

A critical problem during the maintenance optimisation of series-parallel systems is the large strategy space. To address this issue, existing research largely relies on heuristic algorithms, e.g. genetic algorithm (GA) and ant colony optimisation (ACO). These heuristic algorithms can have a low convergence speed, and the obtained strategy are often not global optimal. Instead of searching an optimal strategy in a large space, this paper focuses on the reduction of optimisation space. After investigating the performance dependence among subsystems, this research develops a new strategy space reduction criterion based on the average revenue difference boundaries. By combining the proposed criterion and an earlier method developed by the authors which is based on the stochastic ordering [1], this research develops an efficient maintenance optimisation algorithm. The simulation study shows that the developed maintenance optimisation algorithm can reduce the strategy space more considerably than that proposed in [1].

Optimal Quasi-Periodic Preventive Maintenance Policies for a Two-unit Series System with Dynamic Maintenance Plan

Most research on preventive maintenance (PM) assumed that a PM interval is a fixed value. However, practical PM actions usually are affected by some internal and external random factors, which make the PM interval become a limited random value rather then a fixed value. Few of the existing research consider this situation for two-unit system in their models. In this paper, a quasi-periodic PM policy for one type of two-unit series system with a dynamic maintenance plan is proposed, in which PM for U 1 is perfect whereas for U 2 is imperfect, and the dynamic PM plan is executed in each implemented period, and PM activities are performed through competing results of the dynamic PM plan and a catastrophic failure of U 2. The optimal implemented period of PM and PM number is obtained which minimizes the excepted cost per unit time of the system in long run. Finally, a numerical example is given to illustrate the proposed model.

An optimal policy for maintenance, intermediate buffer, and spare parts

Most research on maintenance is devoted to separate maintenance policy, and some other is focused on maintenance optimization with buffer or spare parts considered. However, there is no existing research taking into account maintenance, buffer, and spare parts together. In this paper, an optimal policy is proposed for a production-inventory system, in which the buffer size, the initial time of buffer accumulation, the predetermine age for preventive maintenance, and the spare part arrival time are optimized together by using Monte Carlo simulation and enumeration method. Numerical examples are delivered for sensitivity analysis of key system parameters. Additionally, the same value of minimal long-term expected cost rate is obtained during repetitive optimizations, which can be considered as the accuracy verification of proposed method.