A Manufacturing Big Data Solution for Active Preventive Maintenance

TLDR

Industry 4.0 is gaining traction thanks to cyber‑physical systems, big data, cloud computing, and industrial wireless networks, while intelligent manufacturing is reshaping product lifecycle management. The paper proposes and implements a manufacturing big‑data solution for active preventive maintenance in industrial settings. The authors design a system architecture that collects manufacturing data, processes it in the cloud, and applies real‑time active maintenance and offline predictive analytics, then evaluate it on a prototype platform against conventional methods. The active preventive maintenance approach accelerates Industry 4.0 adoption.

Abstract

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.