...
首页> 外文期刊>International Journal of Intelligent Enterprise >Decision support system for maximum availability of series-parallel system using particle swarm optimisation
【24h】

Decision support system for maximum availability of series-parallel system using particle swarm optimisation

机译:决策支持系统,利用粒子群算法实现串联-并联系统的最大可用性

获取原文
获取原文并翻译 | 示例
           

摘要

The scope of the present study is to compute optimal availability of various systems of an existing brewery plant using particle swarm optimisation technique. The aim of research paper is focused towards development of structural and mathematical modelling of concerned systems using Markov method in order to examine the criticality of various sub-systems/components and to devise maintenance plans and strategies. In order to achieve the major objectives, the research work is limited to a case study of an existing brewery plant located in the nearby region and repairable systems only. Exponential distribution is used to define the availability importance measures assuming that the failure and repair rates are constant for steady state analysis. In order to explore various possible combinations of random failure and repair rate to achieve optimal availability of a system, an evolutionary optimisation technique, i.e., particle swarm optimisation (PSO) is applied for the first time. The technique is validated by comparing the results obtained for optimal availability with that of existing optimising technique, i.e., genetic algorithm and Markov method. It is established that the results are useful for plant personnel for analysing system behaviour and thereby to improve the system performance by adopting suitable maintenance schedule and strategies.
机译:本研究的范围是使用粒子群优化技术来计算现有啤酒厂各种系统的最佳可用性。研究论文的目的在于使用马尔可夫方法开发相关系统的结构和数学模型,以检查各种子系统/组件的关键性并制定维护计划和策略。为了实现主要目标,研究工作仅限于对位于附近地区的现有啤酒厂和仅可修复系统的案例研究。假设故障和修复率对于稳态分析而言是恒定的,则使用指数分布来定义可用性重要性度量。为了探索随机故障和修复率的各种可能组合以实现系统的最佳可用性,首次应用了进化优化技术,即粒子群优化(PSO)。通过将获得的最佳可用性结果与现有的优化技术即遗传算法和马尔可夫方法进行比较,可以验证该技术的有效性。可以确定的是,这些结果对于工厂人员分析系统行为并通过采用适当的维护计划和策略来提高系统性能很有用。

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