• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Reliability Engineering & System Safety >A simulation based optimization approach for spare parts forecasting and selective maintenance
【24h】

A simulation based optimization approach for spare parts forecasting and selective maintenance

机译：基于仿真的零件预测和选择性维护优化方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Equipment of the Army encounters various modes of exploitation depending on the scenario in which it is used. Typically, the missions are followed by intervals which can be used for maintenance. This is a suitable condition for employment of selective maintenance strategy. However, this maintenance interval is bound by the constraints of time, resources and desired reliability before the start of the next mission. This calls for optimization of maintenance activities that can be fitted into the maintenance break. There is also a requirement of having a forecasting technique for reducing the supply lead times. This paper lays out a methodology to use simulation for predicting failures in the army equipment. A Genetic Algorithm (GA) based approach is then used for optimizing the maintenance activities before the start of the maintenance break. The process of Simulation plus GA Optimization is automated using a program in MATLAB. The novelty of the work lies in modifying the process of Simulation and GA Optimization to suit the exact modus operandi employed by the Army in deploying equipment for peace, training exercise and war (mission with or without some maintenance break) separately. In addition to optimizing the maintenance activities, the methodology also helps in forecasting the requirement of spare parts both before and during the mission. (C) 2017 Elsevier Ltd. All rights reserved.
机译：军队的装备会根据使用场景而遭受各种利用方式。通常，在任务之后是可以用于维护的间隔。这是采用选择性维护策略的合适条件。但是，该维护间隔受下一次任务开始之前的时间，资源和所需可靠性的约束。这就要求优化维护活动，以使其适合于维护中断。还需要具有预测技术以减少供应提前期。本文提出了一种使用仿真方法来预测军队装备故障的方法。然后，基于遗传算法（GA）的方法可用于在维护中断开始之前优化维护活动。使用MATLAB中的程序可自动执行“仿真加GA优化”过程。这项工作的新颖之处在于修改了模拟和遗传算法优化的过程，以适应陆军分别用于部署装备用于和平，训练演习和战争（执行任务或不进行维护）的确切方式。除了优化维护活动外，该方法还有助于预测任务之前和期间的备件需求。 （C）2017 Elsevier Ltd.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号