Research On Scheduling Method Of Manufacturing Equipment Service For Production And Energy Joint Optimization

Both sustainable manufacturing and manufacturing service are the developing trends in manufacturing industry, which can reduce the resource cost and energy consumption in manufacturing process, and also improve the flexibility and responding speed for customers, as well as the production efficiency. The key problems of traditional manufacturing are the huge waste of resources and energy and low production efficiency, which are caused by unscientific scheduling and management for the equipments in the shop. For the new model of services manufacturing, it is significantly important to improve the sustainability by reducing the energy and resource waste and increasing the productivity in a job shop. In order to promote the sustainable manufacturing level in the service-oriented manufacturing job shop, this thesis presents an equipment joint mathematical model of energy consumption and production efficiency. The equipment condition is monitored in real-time, and an optimal manufacturing service dynamic scheduling method is developed. The main research contents are as followed:(1) The production and energy joint model is developed. The influence factors of the equipment manufacturing process was analyzed, then the suitable perception methods of various types production and energy were proposed, the service and virtualization methods of manufacturing equipments, and the multi-objective optimization mathematical model are provided with five important objectives.(2) The dynamic scheduling method of manufacturing equipment service for production and energy joint optimization is proposed. Considering the dynamic changes of the manufacturing equipment service, the disturbance factors of manufacturing process are analyzed, and a dynamic manufacturing service scheduling strategy based on perception data is proposed. In order to solve the dynamic scheduling problem of multi-objective manufacturing service, an enhanced pareto-based bees algorithm is proposed. To ensure the groups variety, prevent the premature convergence and improve search speed, many key technologies are used such as variable neighborhood search, mutation and crossover operation, fast non-dominated ranking, critical path local search, archive pareto set, critical path taboo set. Finally, the proposed method is evaluated in three dynamic scenarios based on Matlab and compared with the existing algorithms.This paper researches on job-shop manufacturing equipment service dynamic scheduling method to provide production and energy joint optimization theoretical and technical foundation, which could improve production efficiency and save energy, and increase the level of sustainable manufacturing in workshop.