Abstract: An industrial equipment management system for predictive maintenance is developed to solve the problems of chaotic equipment management and high maintenance costs in the manufacturing industry.The system is developed based on SpringBoot framework and Vue front-end separation mode that the coupling is reduced;the equipment management module is designed according to the actual production that realizes the basic information and production data management of the equipment.A good front-end interface for human-computer interaction is developed to achieve the purpose of visual management of equipment information.The data storage module is designed through integrating multiple databases to solve the problem of reading and writing different types of data in the system.The equipment maintenance module is designed based on the Spark big data processing framework to perform online analysis of equipment real-time data.In order to achieve the goal of predictive maintenance of equipment,machine learning regression algorithms are used to train predictive models on historical data to achieve real-time monitoring of equipment status and prediction of remaining life.Finally,the feasibility of the designed management system is verified by industrial robot equipment experiments.

Key words: Big data processing, Equipment management, Machine learning, Predictive maintenance, Spark