In many parts factories, there is a large quantity of casting and machining equipment. In the past, manual paper-based data statistics were mainly used, making management difficult. Equipment capacity utilization cannot be accurately evaluated, and real-time equipment status cannot be monitored. In a certain auto parts factory, process parameters (temperature, speed, etc.) cannot be obtained in real-time, making quality control difficult and unable to prevent errors. Moreover, inspection equipment data cannot be collected in real-time, leading to inability to stop production immediately when quality issues occur.
Through the data collection, data management, configuration modeling, rule engine, and other functions provided by the GETECH IoT platform, the business objective of collecting and monitoring the operating status, process parameters, and environmental parameters of core equipment in the factory workshop has been achieved. Currently, workshop managers can monitor production dynamics and equipment health in real-time through various channels such as large screens and mobile phones; on-site production personnel can also timely understand the inspection results of semi-finished products, make parameter adjustments based on data, and automatically control equipment to avoid the occurrence of defective products due to non-compliant parameters.
