模糊建模和成本优化故障耐受系统与服务中断的系统
Vijay Pratap Singh1, Madhu Jain1, Rakesh Kumar Meena2
1Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee 247667, India.
ISA transactions
|December 27, 2024
概括
本研究引入了一个非马尔科夫模型,用于容错加工系统 (FTMS) 预测性能和优化设计. 它解决了不完美的维修问题,并使用了优化技术来降低成本.
科学领域:
- 工业工程 工业工程 工业工程
- 运营研究 运营研究
- 可靠性工程可靠性工程
背景情况:
- 耐故障加工系统 (FTMS) 对于需要高可靠性的行业至关重要.
- 现有的模型可能无法完全捕捉FTMS中复杂的故障和维修场景.
- 系统的可用性和可维护性是关键性能指标.
研究的目的:
- 为FTMS开发一个非马尔科夫队列模型,使用服务器假期,故障和不完美的维修.
- 用有限人群M/G/1排队模型分析预测FTMS的性能.
- 通过使用元启发式和经典优化技术来最大限度地降低总成本,优化FTMS设计.
主要方法:
- 开发一个非马科夫队列模型,包括服务器休假,故障和不完美的维修流程.
- 在M/G/1排队模型的分析解决方案中应用补充变量技术.
- 实现参数非线性编程,粒子集群优化 (PSO),遗传算法 (GA) 和准牛顿方法用于性能评估和优化.
主要成果:
- 为FTMS的性能预测得出了一个分析解决方案.
- 性能指标在清晰和模糊环境中进行了评估.
- 通过使用各种优化技术来最大限度地降低总成本来确定最佳设计描述符.
- 对性能指数进行了对系统参数的敏感性分析.
结论:
- 开发的非马尔科夫模型为分析具有复杂故障和维修动态的FTMS提供了强大的框架.
- 优化技术有效地确定了成本效益高的FTMS的最佳设计参数.
- 该研究为提高工业加工系统的可靠性和可维护性提供了宝贵的见解.
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