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Fleet-level selective maintenance problem under a phased mission scheme with short breaks: A heuristic sequential game approach

机译:具有短期休息的分阶段任务计划下的舰队级选择性维护问题:启发式顺序博弈方法

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Selective maintenance is the most widely used strategy for identifying and performing the maintenance actions necessary for fleet mission success. A fleet of equipment is usually required to perform phased missions with short scheduled breaks. In this case, a selective maintenance model should be extended for frequency-based maintenance optimization. We research the problem considering the application of condition-based maintenance (CBM). The problem is formulated with the objective of reducing the repair frequency and cost. The constraint is the reliability of the phased mission, and the variables are the remaining useful lifetimes (RUL) of all the key subsystems. The equipment can be classified into three echelons based on the health status before each wave of a mission, and a heuristic game framework with state backtracking is proposed for the three echelons to solve the problem. The flowchart and heuristic rules of the game framework are given, and the game algorithms for the second and third echelons are presented. The second echelon algorithm aims to select the dispatched equipment for the current wave and minimize maintenance, and the third echelon algorithm aims to ensure that sufficient equipment is available for the next wave by performing necessary maintenance. Finally, we present two types of strategy adjustment methods with state backtracking to turn infeasible solutions into feasible solutions and to optimize feasible solutions. To verify the capacity of the proposed method, a case involving a fleet of 12 aircraft is analyzed for a three-mission scheme, and the aircraft repair times and costs are reduced by the method.
机译:选择性维护是用于识别和执行舰队任务成功所需的维护行动的最广泛使用的策略。通常需要一批设备来执行短期计划的分阶段任务。在这种情况下,应该扩展选择性维护模型以基于频率的维护优化。考虑到基于状态的维护(CBM)的应用,我们研究了该问题。解决该问题的目的是减少维修频率和成本。约束条件是分阶段任务的可靠性,变量是所有关键子系统的剩余使用寿命(RUL)。根据每次任务执行前的健康状况,设备可以分为三个梯队,并针对三个梯队提出了一种具有状态回溯的启发式游戏框架,以解决该问题。给出了游戏框架的流程图和启发式规则,并给出了第二,第三梯队的游戏算法。第二种梯队算法的目的是为当前浪潮选择派遣的设备,并最大程度地减少维护,而第三种梯队算法的目的是通过执行必要的维护,确保为下一波浪提供足够的设备。最后,我们提出两种带有状态回溯的策略调整方法,以将不可行的解决方案转变为可行的解决方案并优化可行的解决方案。为了验证所提出方法的能力,分析了一个由12架飞机组成的机队的三任务方案,该方法减少了飞机的维修时间和成本。

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