基于遗传算法的水泥工业磨粉机系统维护优化

M. Mahadevan, T. P. Robert
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引用次数: 1

摘要

本文描述了一种利用遗传算法(GA)推导工艺装置最优维修计划的维修优化框架。考虑的两种可能的替代方案是:不完善的维护和更换。维护模型包含了纠正性维护和预防性维护。采用遗传算法搜索启发式优化维修或更换的选择,以实现成本最小和目标可靠性。用蒙特卡罗模拟法根据成本的现值对模型进行了评价。蒙特卡罗方法的灵活性允许包括几个实际方面,如恶化修理,老化和服务变化。这项研究是在印度泰米尔纳德邦一家水泥工业的原料厂进行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Maintenance optimisation in a cement industry raw-mill system using genetic algorithm
This paper describes a maintenance optimisation framework for deriving optimal maintenance schedule for a process plant using genetic algorithm (GA). The two possible alternatives considered are: imperfect maintenance and replacement. The maintenance model incorporates both the corrective maintenance and preventive maintenance actions. GA search heuristic is used to optimise the choice of maintenance or replacement to achieve the minimum cost with target reliability. The model is evaluated by Monte Carlo simulation in terms of present value of the cost. The flexibility of the Monte Carlo method allows the inclusion of several practical aspects such as deteriorating repairs, aging and service variations. This study is carried out in the raw-mill section of a cement industry in Tamil Nadu, India.
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