Fourth Industrial Revolution has brought in a new era of smart manufacturing, wherein, application of Internet of Things , and data-driven methodologies is revolutionizing the conventional maintenance. With the help of real-time data from the IoT and machine learning algorithms, predictive maintenance allows industrial systems to predict failures and optimize machines life. This paper presents the synergy between the Internet of Things and predictive maintenance in industrial engineering with an emphasis on the technologies, methodologies, as well as data analytics techniques, that constitute the integration. A systematic collection, processing, and predictive modeling of data is discussed. The outcomes emphasize greater operational efficiency, decreased downtime, and cost-saving, which makes a good argument as to why predictive maintenance should be implemented in contemporary industries.

翻译：第四次工业革命开启了智能制造的新纪元，其中物联网的应用与数据驱动方法正在彻底改变传统维护模式。借助物联网实时数据与机器学习算法，预测性维护使工业系统能够预测故障并优化设备寿命。本文阐述了工业工程中物联网与预测性维护的协同作用，重点探讨了构成该集成的关键技术、方法论及数据分析技术。文中系统论述了数据的收集、处理与预测建模过程。研究结果突显了提升运营效率、减少停机时间与节约成本的显著优势，为预测性维护在现代工业中的实施提供了有力依据。