A Research Of Multi-Objective Dynamic Production Scheduling Based On Critical Chain

Production scheduling is the core of production management system of the manufacturing enterprise, but also the key factors that affect the production efficiency.Therefore,solving the problem of production scheduling is very important for shortening the production period, improving the enterprise competitiveness and customer satisfaction, and controling the cost. However, production scheduling has become a very challenging task due to uncertainties in the production process, such as the shorter production cycles and faster process changes caused by the introduction of new production processes, the updates of products, the unpredictable equipment failure,the changes of customer delivery time, and the drift of bottleneck equipment, etc. These dynamic factors and their interaction has brought a lot of complex dynamic uncertainty to the manufacturing process of the manufacturing enterprise and led to the frequent fluctuates of the performance of production systems in manufacturing enterprises and enormous difficulties of production scheduling on the effective control of the production process.Supported by the National Natural Science Foundation of China, "Research on performance prediction and optimization of semiconductor manufacturing systems based on variability" (Grant No. 71671026), this thesis made full use of the variability basics of factory physics to provide a reference method to reduce the process processing time. Calculating the process priority according to the customer importance and order priority achieved the goal of maximizing production efficiency. It was more in line with the actual production of complex environment to improve the buffer set with the variability basics and resource utilization and use the heuristic algorithm to solve the critical chain of production plans. Ultimately compiling the software system achieved the multi-target production scheduling and ensured stable production of enterprises at the same time achieved the maximum production efficiency.Firstly, buffering variabilities of the processes with the variability basics of factory physics and improving the method of shortening the processing time. Secondly,realizing the goal of maximizing the production efficiency of the customer’s importance,order and process priority by designing the priority rules for the characteristics of mixed-flow production, and sorting the production process by the priority rule to generate the initial production plan. This thesis adjusted the initial production plan with the critical chain identification method and found out the critical chain under the resource constraints and priority constraints.Then, this thesis measured the qualitative and quantitative measures of process processing time variability and mutual influence in production process with the variability basics of factory physics,set buffer of the adjusted production scheduling plan with the change of the variability result and process resource utilization and finally built a multi-objective production scheduling model based on the critical chain.Based on the above research, this thesis solved the model with the particle swarm optimization combined with the genetic operation, and proved that the model could schedule the mixed flow production line of an air conditioner heat exchanger manufacturer effectively and enhance the production efficiency and economic efficiency with the design of the prototype system.