Task Scheduling Energy-Saving Optimization Support System With Process Routing Flexibility For Machining Job-shop

Machining job-shop are composed of computerized numerical control machines or manual machines for producing workpieces. Since machining is used for removing material of workpieces, it is wasteful in use of energy and quit inefficient. The environmental burden caused by energy consumption during the use phase of machining job-shop could be reduced by energy-saving research. Hence reducing the energy consumption of machining job-shop is one of the strategies and the hot research issues for sustainable manufacturing.From the perspective of production operation layer, the energy consumption could be saved through the reasonable scheduling of production tasks in the production process for machining job-shop. The advantage is that machine tools and layout of the machining job-shop will not be change and it is easier to implement. The existing researches of scheduling method considering energy consumption for machining job-shop focus on constant or partly flexible process plan, and the study considering multi flexibilities(e.g. operation flexibility, sequencing flexibility and processing flexibility) of process plan is scarce. Therefore, this paper studied the task scheduling energy-saving optimization problem with process routing flexibility for machining job shop, and presented a Task scheduling energy-saving optimization support system with process routing flexibility for machining job-shop. The study includes the following sections.First, the features of flexible process plan for machining job-shop are elaborated, and a framework of task scheduling energy-saving optimization method with process routing flexibility for machining job-shop is proposed which considers the influence that flexible process plan have on energy consumption during scheduling of machining job-shop. The architecture, functional modules and databases of the system are designed based the framework.Then, some key technologies of the system have studied, which including the multi-objective mathematical model of task scheduling energy-saving optimization with process routing flexibility for machining job-shop and an improved Q-learning algorithm for multi-objective Pareto solving. The mathematical model is formulated using the energy consumption objective, the makespan objective and the machine load objective. The algorithm is improved to find the Pareto optimal solution with the balance of multi objectives.Finally, based the above study, task scheduling energy-saving optimization support system with process routing flexibility for machining job-shop has developed, which including the detailed functional modules and databases of the system. A case study was implemented to compare the makespan, energy consumption and machine load value of the scheduling schemes between before and after optimization, which showed the effectiveness and feasibility of the system.