Article Details

Abstract

To address the problems of difficult multi-equipment collaborative scheduling and dispersed operation monitoring in intelligent warehouse systems, an equipment scheduling and monitoring system integrating PLC and Internet of Things (IoT) is proposed. A unified equipment state model is constructed, and a mapping mechanism from PLC operational data to the state model is designed. On this basis, an event-driven equipment scheduling method is proposed, and a real-time monitoring and anomaly perception mechanism based on the IoT platform is developed. An experimental platform integrating 15 devices including stacker cranes is established to compare the event-driven scheduling method with the periodic polling scheduling method. The results show that the average task completion time decreases from 124.6 s to 108.4 s, the equipment utilization rate increases from 72.3% to 81.7%, and the system throughput increases from 173 to 201 tasks per hour. The average delay of the monitoring system state update is 126 ms. The system can effectively improve equipment scheduling efficiency and meet the real-time monitoring requirements of warehouse operations.

Keywords

intelligent warehouse; PLC; equipment scheduling; operation monitoring

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About the authors

Ma Linxi (born on July 10, 1987), male, Han nationality, from Dali, Shaanxi, is a senior engineer with a master's degree. His research direction is industrial automation - intelligent warehousing equipment.