Three-Stage Optimisation Method For Concurrent Manufacturing Energy Data Collection

Real-time data collection based on large energy sensor networks (ESN) is the foundation of smart energy-efficient manufacturing (SEEM). However, the serial communication interface RS485 in ESN reduces the collection efficiency due to the restriction of concurrency of multiprocessors. In order to overcome the restriction, this paper presents a three-stage optimisation method for the scheduling of data collection jobs. Data collection jobs are divided into concurrent sub-jobs and serial sub-jobs. Aiming at reducing collection completion time which is evaluated by a time Petri net model, the three-stage optimisation model for the scheduling of two types of sub-jobs is then established. The optimisation model consisting of assigning RS485 bus to processor, adjusting DCJ among processors and adjusting DCJ sequence will minimise the completion time of data collection jobs through combining greedy algorithm with generic algorithm. Test experiments show that the proposed model is able to improve concurrent efficiency by more than 50% compared to traditional DCJ collection method which regards RS485 bus as an assigned unit. An application case shows that the proposed model dropped the completion time from 9.8s to 6.0s, and the real-time performance can support identifying standby, machine failure, energy leakage, and in real time.