Study On The Strategy Of Job Release For Mould Workshop In Random Environment

In recent years, with the development of the world's free trade and global economic integration, competition between manufacturers of MTO (Make To Order, referred to as MTO) is growing, for these manufacturers, besides reducing the costs of production, they must shorten product life cycle and ensure product delivery on time, this has become one of most important conditions for the survival and development of MTO manufacturing enterprises. Higher demand is given by the control of delivery to the planning and control system of mold manufacturing, but the current popular manufacturing planning and control technology can neither effectively adapt to the mold manufacturer, nor shorten product life cycle or ensure product delivery on time, so, the research on manufacturing planning and control technology which could be effectively applied to the mold manufacturer has very important significance.For the production environment of highly complex tasks, such as workshops and MTO manufacturing industry, methods of production planning and control (Production Planning and Control, referred to as PPC) called Load Control (Workload Control, referred to as WLC) have been proposed. Job release control includes input control and output control, input control determines three aspects of the tasks in the pool:the beginning time of production, the amount of releasing in each cycle, and the choice of which tasks released to the shop floor. There have been many methods about the control of job releasing, but in view of the random environment of the job release control in workshop, the methods have been not existed yet. With the production planning and control system in a large mold enterprise as the background, strategies of job releasing are presented to adapt to the random environment in mold workshop. Firstly, this paper develops a method for determining the workshop equivalent of process times of the bottleneck resources, and it has been proved through the simulation results. Then, it further proposes a method for determining the workload upper bound range for above bottleneck resources, and a simulation-based approach is presented for searching the precision value of the upper bound from above range Finally, the method of choosing tasks is proposed, and simulation results have shown that the presented method is reasonable and efficient.