Research On Dynamic Job Shop Scheduling Optimization Algorithm Of Single And Small Batch Manufacturing Execution System

Manufacturing execution system is a workshop production management technology and real-time information system between plan management and industrial control layer, which mainly solves the problem to perform the production task of the workshop. In the view of the current economic situation,the main mode of production of small and medium enterprises concentrated in single and small batch production, how to combine the single and small batch production and MES, this research is currently a hot topic. MES is important for the production of high efficiency, high-quality products, low consumption. In the single and small batch MES, the job shop planning and scheduling dominate the internal process of MES and it is the center of the MES connected with the external system, advanced core technology of MES represented by job shop planning and scheduling optimization, Therefore MES job shop planning and scheduling optimization has been one of the hotspots of research, planning and management of the manufacturing execution system. However, due to the presence of job shop planning and scheduling production load balancing complex,difficult to estimate the operation plan, control complex job scheduling and other issues, bring great difficulties and challenges to actual production.Special demand of this paper for single and small batch MES environment job shop planning and scheduling optimization, study on single and small batch MES dynamic job shop planning and scheduling optimization algorithm, and construct a practical job shop scheduling optimization algorithm of single and small batch MES. By increasing intelligence, agility, robustness and flexibility of dynamic job planning and scheduling optimization to improve its usefulness, the study has important theoretical significance and application value.Firstly, according to the characteristics of existing emergency factors of single and small batch MES production process, the minimum makespan as measures, we proposed a distributed particle swarm optimization algorithm aiming to solve single objective job shop scheduling problem. The algorithm adopts the method of distributed ideas to solve problems and we are established for two multi-agent particle swarm optimization model in this algorithm, it can solve the traditional particle swarm optimization algorithm when making decisions in real time according to the emergencies. Finally, some benthmark problems were experimented and the results are compared with the traditional algorithm. Experimental results proved that the developed distributed PSO is enough effective and efficient to solve the JSP and it also verified the reasonableness of the multi-agent particle swarm optimization model.Then for single and small batch MES in the process of production,jobs due to machine failures, temporary processing task changes and other dynamic events will terminate the processing, which requires to jobs for rescheduling, with efficiency and stability as the goal as the scheduling criterion, to construct a multi-objective dynamic scheduling mathematical model. And according to the model proposed a multi-objective dynamic scheduling algorithm of genetic algorithm combined with rolling window strategy, for the convenience of real-time to the termination of the jobs processing of dynamic adjustment and to improve the workshop on emergency reaction ability and operation quality.Finally, according to single and small batch manufacturing in a company,developed a single and small batch MES dynamic job planning and scheduling optimization system, to realize the operation monitoring and dynamic scheduling and optimization schemes for organic, control and adjustment of closed-loop system structure, and combined with job shop planning and scheduling problems were real case studies.