论文标题
事件日志的预测维护：ATM机队的应用
Predictive maintenance on event logs: Application on an ATM fleet
论文作者
论文摘要
预测维护用于工业应用中，以提高机器可用性并优化与计划外维护相关的成本。在大多数情况下，预测维护应用程序使用传感器的输出，记录物理现象，例如温度或振动，可以直接链接到机器的降解过程。但是，在某些应用程序中，不可用传感器的输出，而使用机器生成的事件日志。我们首先研究了文献中用于解决预测性维护问题的方法，并提出了一个新的公共数据集，其中包含来自156台机器的事件日志。此后，我们为预测维护系统定义了一个评估框架，该框架考虑了业务限制，并进行实验以探索合适的解决方案，该解决方案可以用作使用此新数据集的未来工作的指南。
Predictive maintenance is used in industrial applications to increase machine availability and optimize cost related to unplanned maintenance. In most cases, predictive maintenance applications use output from sensors, recording physical phenomenons such as temperature or vibration which can be directly linked to the degradation process of the machine. However, in some applications, outputs from sensors are not available, and event logs generated by the machine are used instead. We first study the approaches used in the literature to solve predictive maintenance problems and present a new public dataset containing the event logs from 156 machines. After this, we define an evaluation framework for predictive maintenance systems, which takes into account business constraints, and conduct experiments to explore suitable solutions, which can serve as guidelines for future works using this new dataset.
