A Predictive Maintenance Solution for Bearing Production Line Based on Edge-Cloud Cooperation

Effective and accurate maintenance of equipment is a difficult problem for the manufacturing industry. With the development of technologies such as the Internet of Things, artificial intelligence, and edge computing, predictive maintenance (PdM) has brought new solutions to this problem. Taking the bearing production line as the application object, this paper proposes a predictive maintenance solution of “edge cloud coordination”. By deploying sensors in the production line equipment to realize equipment data collection, data cleaning, data standardization and real-time control are completed at the edge end. The cloud analyzes the data through machine learning algorithms to predict equipment failure and remaining service life, thereby reducing equipment maintenance costs and improving equipment utilization. Experiments show that this solution provides a powerful means to ensure efficient and stable operation of the bearing production line, which can effectively predict equipment failure and equipment life, and reduce operation and maintenance costs, with feasibility and good market application prospects.