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Reliability-Centered Maintenance of the Electrically Insulated Railway Joint via Fault Tree Analysis: A Practical Experience Report

机译:通过故障树分析对以电气为中心的电气绝缘接头进行以可靠性为中心的维护:实践经验报告

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Maintenance is an important way to increase system dependability: timely inspections, repairs and renewals can significantly increase a system's reliability, availability and life time. At the same time, maintenance incurs costs and planned downtime. Thus, good maintenance planning has to balance between these factors. In this paper, we study the effect of different maintenance strategies on the electrically insulated railway joint (EI-joint), a critical asset in railroad tracks for train detection, and a relative frequent cause for train disruptions. Together with experts in maintenance engineering, we have modeled the EI-joint as a fault maintenance tree (FMT), i.e. a fault tree augmented with maintenance aspects. We show how complex maintenance concepts, such as condition-based maintenance with periodic inspections, are naturally modeled by FMTs, and how several key performance indicators, such as the system reliability, number of failures, and costs, can be analysed. The faithfulness of quantitative analyses heavily depend on the accuracy of the parameter values in the models. Here, we have been in the unique situation that extensive data could be collected, both from incident registration databases, as well as from interviews with domain experts from several companies. This made that we could construct a model that faithfully predicts the expected number of failures at system level. Our analysis shows that that the current maintenance policy is close to cost-optimal. It is possible to increase joint reliability, e.g. by performing more inspections, but the additional maintenance costs outweigh the reduced cost of failures.
机译:维护是提高系统可靠性的重要方法:及时检查,维修和更新可以显着提高系统的可靠性,可用性和使用寿命。同时,维护会增加成本和计划内的停机时间。因此,良好的维护计划必须在这些因素之间取得平衡。在本文中,我们研究了不同维护策略对电绝缘铁路接头(EI接头),火车检测中铁轨中的一项重要资产以及火车中断的相对频繁原因的影响。我们与维护工程专家一起,将EI关节建模为故障维护树(FMT),即以维护方面为基础的故障树。我们展示了FMT如何自然地建模复杂的维护概念,例如基于状态的维护和定期检查,以及如何分析几个关键性能指标,例如系统可靠性,故障数量和成本。定量分析的真实性在很大程度上取决于模型中参数值的准确性。在这里,我们处于一种独特的情况下,即可以从事件注册数据库,也可以通过对来自多家公司的领域专家的采访来收集大量数据。这使得我们可以构建一个模型,该模型能够忠实地预测系统级别的预期故障数。我们的分析表明,当前的维护策略已接近最佳成本。例如,可以提高接头的可靠性。通过执行更多检查,但额外的维护成本超过了减少的故障成本。

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