当前位置:
X-MOL 学术
›
Proc. Inst. Mech. Eng. Part O J. Risk Reliab.
›
论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Optimizing preventive maintenance policy: A data-driven application for a light rail braking system
Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability ( IF 2.1 ) Pub Date : 2017-06-19 , DOI: 10.1177/1748006x17712662 Francesco Corman 1 , Sander Kraijema 1, 2 , Milinko Godjevac 1 , Gabriel Lodewijks 1
Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability ( IF 2.1 ) Pub Date : 2017-06-19 , DOI: 10.1177/1748006x17712662 Francesco Corman 1 , Sander Kraijema 1, 2 , Milinko Godjevac 1 , Gabriel Lodewijks 1
Affiliation
This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions.
中文翻译:
优化预防性维护策略:数据驱动的轻轨制动系统应用
本文提供了一个案例研究,该案例从可靠性,可用性和维护成本的角度确定了轻轨车辆系统的最佳预防性维护策略。维护策略以固定的基于时间的间隔为制动系统的每个子系统定义了三个预定义的预防性维护操作之一。基于工作,维护和故障数据,我们通过Weibull分布对当前维护策略下系统及其子系统的可靠性下降进行建模。然后,我们分析确定可靠性,可用性和维护成本之间的关系。我们根据记录的可靠性和可用性验证模型,并通过专门的敏感性分析获得进一步的见解。然后在顺序优化框架中使用该模型,确定预防性维护间隔以改善关键性能指标。我们展示了数据驱动的模型确定最佳维护策略的潜力:通过延长间隔时间和重新分组维护操作,可以在降低30%维护成本的情况下实现相同的系统可用性和可靠性。
更新日期:2017-06-19
中文翻译:
优化预防性维护策略:数据驱动的轻轨制动系统应用
本文提供了一个案例研究,该案例从可靠性,可用性和维护成本的角度确定了轻轨车辆系统的最佳预防性维护策略。维护策略以固定的基于时间的间隔为制动系统的每个子系统定义了三个预定义的预防性维护操作之一。基于工作,维护和故障数据,我们通过Weibull分布对当前维护策略下系统及其子系统的可靠性下降进行建模。然后,我们分析确定可靠性,可用性和维护成本之间的关系。我们根据记录的可靠性和可用性验证模型,并通过专门的敏感性分析获得进一步的见解。然后在顺序优化框架中使用该模型,确定预防性维护间隔以改善关键性能指标。我们展示了数据驱动的模型确定最佳维护策略的潜力:通过延长间隔时间和重新分组维护操作,可以在降低30%维护成本的情况下实现相同的系统可用性和可靠性。