选择测试和维护策略,以最低的生命周期成本实现可用性目标

P. Dersin, A. Peronne, C. Arroum
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引用次数: 14

摘要

复杂系统的操作员,例如在航空航天、电力网络、自动化制造或铁路行业中发现的,施加了更严格的可用性性能约束。与此同时,全寿命周期成本(LCC)也越来越受到人们的关注。阿尔斯通交通信息解决方案公司的URBALIS自动化轨道交通系统就面临着这种情况。这导致RAM部门调查影响可用性和LCC的一些关键因素,以便为设计人员和维护人员提供以最低成本达到可用性目标的指导方针。冗余需要管理:特别是在功能完全丢失之前能够检测到部分冗余丢失是至关重要的。这就是可测试性和维护策略发挥作用的地方。在第一个模型中,假设故障率恒定且完全维护,并使用马尔可夫模型。为了考虑非恒定故障率情况,以及计划维护检查的确定性方面,然后使用Petri网进行模拟。还考虑了不完善的维护模型(基于木岛的虚拟年龄),以便考虑与维护相关的老化的影响。因此,根据相对的单位投资成本、纠正性和预防性维护制定了建议,并根据故障率、测试覆盖率以及完美维护的百分比对系统可用性进行了敏感性分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Selecting test and maintenance strategies to achieve availability target with lowest life-cycle cost
Operators of complex systems, such as are found in aerospace, electric power networks, automated manufacturing, or the railways industry, impose ever more stringent availability performance constraints. At the same time, increasing attention is being paid to life-cycle cost (LCC). ALSTOM Transport Information Solutions' URBALIS automated mass transit system is confronted with this situation. This has led the RAM Department to investigating some key factors which impact availability and LCC, in order to provide designers and maintainers with guidelines for reaching availability targets at lowest cost. Redundancy needs to be managed: in particular it is crucial to be able to detect a partial loss of redundancy before the function is completely lost. This is where testability and maintenance policy come into play. In a first model, constant failure rate and perfect maintenance are assumed and Markov modelling is used. In order to contemplate the non-constant failure rate case, as well as the deterministic aspect of scheduled maintenance inspections, simulations are then run with Petri nets. Imperfect maintenance models (based on Kijima's virtual age) are also considered so that the impact of maintenance-related ageing can be taken into account. .Recommendations are thus formulated depending on relative unit costs of investment, corrective and preventive maintenance, and sensitivity analyses of system availability are performed with respect to failure rate, test coverage rate as well as percentage of perfect maintenance.
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