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EN
Maintenance is an important way to ensure the best performance of repairable systems. This paper considers how to reduce system maintenance cost while ensuring consistent system performance. Due to budget constraints, preventive maintenance (PM) can be done on only some of the system components. Also, different selections of components to be maintained can have markedly different effects on system performance. On the basis of the above issues, this paper proposes an importance-based maintenance priority (IBMP) model to guide the selection of PM components. Then the model is extended to find the degree of correlation between two components to be maintained and a joint importance-based maintenance priority (JIBMP) model to guide the selection of opportunistic maintenance (OM) components is proposed. Also, optimization strategies under various conditions are proposed. Finally, a case of 2H2E architecture is used to demonstrate the proposed method. The results show that generators in the 2E layout have the highest maintenance priority, which further explains the difference in the importance of each component in PM.
EN
In the marine industry, heave compensation systems are applied to marine equipment to compensate for the adverse effects of waves and the hydraulic system is usually used as the power system of heave compensation systems. This article introduces importance theory to the opportunistic maintenance (OM) strategy to provide guidance for the maintenance of heave compensation systems. The working principle of a semi-active heave compensation system and the specific working states of its hydraulic components are also first explained. Opportunistic maintenance is applied to the semi-active heave compensation system. Moreover, the joint integrated importance measure (JIIM) between different components at different moments is analyzed and used as the basis for the selection of components on which to perform PM, with the ultimate goal of delaying the degradation of the expected performance of the system. Finally, compared with conditional marginal reliability importance (CMRI)based OM, the effectiveness of JIIM-based OM is verified by the Monte Carlo method.
EN
This paper deals with modeling and analysis of complex mechanical systems that deteriorate with age. As systems age, the questions on their availability and reliability start to surface. The system is believed to suffer from internal stochastic degradation mechanism that is described as a gradual and continuous process of performance deterioration. Therefore, it becomes difficult for maintenance engineer to model such system. Semi-Markov approach is proposed to analyze the degradation of complex mechanical systems. It involves constructing states corresponding to the system functionality status and constructing kernel matrix between the states. The construction of the transition matrix takes the failure rate and repair rate into account. Once the steady-state probability of the embedded Markov chain is computed, one can compute the steady-state solution and finally, the system availability. System models based on perfect repair without opportunistic and with opportunistic maintenance have been developed and the benefits of opportunistic maintenance are quantified in terms of increased system availability. The proposed methodology is demonstrated for a two-stage reciprocating air compressor with intercooler in between, system in series configuration.
EN
A complex system consisting of monitored and non-monitored components is analyzed. Monitored components are subject to a degradation gamma process. Non-monitored components are subject to external failures. A Condition-Based Maintenance and an inspection policy are applied to reduce the impact of the failures in the monitored components. When a failure occurs, maintenance team performs a corrective replacement after a certain delay time. An opportunistic maintenance strategy is also implemented, meaning that a maintenance intervention can be used as an opportunity for preventive maintenance of monitored components. Each maintenance task implies a certain cost and each monitored component is assumed to provide a reward. The expected cost of the whole system is minimized through the optimization of the preventive thresholds and the time between inspections. Numerical examples are obtained from applying a blend of Genetic Algorithm and Monte-Carlo simulation.
EN
In future, offshore wind turbines may be consider a crucial part in the supply of energy. Maintenance processes are directed to attain a safe and reliable operation of offshore machines and wind turbines. In this paper, an opportunistic maintenance strategy for offshore wind turbine is proposed, considering imperfect maintenance and the preventive maintenance durations. Reliability Centric Maintenance serves as a proactive tactic to operations and maintenance by inhibiting the possible reasons of poor performance and controlling failures. Other components can implement the opportunistic preventive maintenances if one component has reached its reliability threshold. According to the rolling horizon approach, it is of great importance to update the maintenance planning for the sake of the short-term information. By figuring out the best combination, the maintenance schedule in the mission time has been finally determined. Failure information are obtained from previous studies to accomplish the calculations. The outcomes indicate that the maintenance cost has been dramatically reduced through the application of opportunistic maintenance.
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