LAUSR

Nowadays, a large amount of energy is consumed by buildings in the city. Among them, industrial energy consumption accounts for a large proportion due to the high power of manufacturing devices in the job-shop. To achieve higher energy-efficiency, lots of scheduling methods in the job-shop are developed. However, most of the current scheduling method is based on the prior-experimental data and the schedule of the production cycle cannot be adjusted according to energy status of manufacturing devices. Thus a dynamic scheduling system based on the cyber-physical energy monitoring system is proposed to improve the energy efficiency of the job-shop. First, a novel process of “scheduling-monitoring-updating-optimizing” is implemented in the proposed system. In the scheduling model, tool aging condition is considered along with the geometry information of the work-piece to estimate energy consumption of the manufacturing process. At last, a modified genetic algorithm with multi-layer coding is applied to generate an energy-efficient schedule. The proposed system is implemented in a production cycle which contains 36 operations of six work-pieces and ten machine tools to prove its validity.