论文标题
一项关于行业预测维护的调查4.0
A Survey on Predictive Maintenance for Industry 4.0
论文作者
论文摘要
2016年大众汽车的生产问题导致每周销售高达4亿欧元的巨大损失。此示例显示了工作生产机构对公司的巨大财务影响。尤其是在具有智能互联机器的工业4.0和工业物联网的数据驱动域中，常规，静态维护时间表似乎是老式的。在本文中，我们介绍了一项有关工业4.0预测维护中最新技术的调查。根据一项结构化的识字调查，我们在行业4.0的背景下提供了预测维护的分类，并讨论了该领域的最新发展。
Production issues at Volkswagen in 2016 lead to dramatic losses in sales of up to 400 million Euros per week. This example shows the huge financial impact of a working production facility for companies. Especially in the data-driven domains of Industry 4.0 and Industrial IoT with intelligent, connected machines, a conventional, static maintenance schedule seems to be old-fashioned. In this paper, we present a survey on the current state of the art in predictive maintenance for Industry 4.0. Based on a structured literate survey, we present a classification of predictive maintenance in the context of Industry 4.0 and discuss recent developments in this area.
