A Manufacturing Big Data Solution for Active Preventive Maintenance

• Published in: IEEE transactions on industrial informatics Vol. 13; no. 4; pp. 2039 - 2047
• Main Authors: Jiafu Wan, Shenglong Tang, Di Li, Shiyong Wang, Chengliang Liu, Abbas, Haider, Vasilakos, Athanasios V.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-08-2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Big Data; Cloud computing; Computer architecture; Cyber-physical systems; Data management; Data processing; Distribuerade datorsystem; Industry 4.0; intelligent manufacturing; Intelligent manufacturing systems; Maintenance management; Manufacturing; Mobile and Pervasive Computing; Preventive maintenance; Product life cycle; Real-time systems; Wireless networks
• ISSN: 1551-3203; 1941-0050; 1941-0050
• DOI: 10.1109/TII.2017.2670505

Industry 4.0 has become more popular due to recent developments in cyber-physical systems, big data, cloud computing, and industrial wireless networks. Intelligent manufacturing has produced a revolutionary change, and evolving applications, such as product lifecycle management, are becoming a reality. In this paper, we propose and implement a manufacturing big data solution for active preventive maintenance in manufacturing environments. First, we provide the system architecture that is used for active preventive maintenance. Then, we analyze the method used for collection of manufacturing big data according to the data characteristics. Subsequently, we perform data processing in the cloud, including the cloud layer architecture, the real-time active maintenance mechanism, and the offline prediction and analysis method. Finally, we analyze a prototype platform and implement experiments to compare the traditionally used method with the proposed active preventive maintenance method. The manufacturing big data method used for active preventive maintenance has the potential to accelerate implementation of Industry 4.0.