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

Manufacturing execution system (MES) which core is job shop scheduling optimization can be used to integrate between enterprise management information and production control information to solve the problem of the information fault between them. Because production environment and information environment of the single and small batch enterprise are very complex, the architecture of MES should be able to solve the adaptivity problem of single and small batch production management, and the job shop scheduling optimization method.should meet many kinds of complex scheduling objectives and dynamically process the uncertain random events during job shop production.With the single and small batch production as research object, a new architecture and job shop scheduling optimization method of single and small batch MES are proposed in this thesis, in order to solve the optimization problem during the whole production process and to archieve optimizing running, controlling and managing the business activities and production activities of the enterprise. The main research work includes the following aspects:According to the characteristics of single and small batch production, a new architecture of single and small batch MES has been proposed; the functional model and the integrated relationship between MES, enterprise resource planning (ERP), and shop floor control (SFC) have been built. Furthermore, the adaptation needs of the single and small batch manufacture to the architecture of MES have been satisfied; the problems of functions overlapping, data heterogeneity, and system complexity caused by the traditional integration have been solved to meet the needs of the enterprises practical application.For solving the problem of job shop planning, work monitoring and plan changing, the job shop scheduling optimization strategy has been proposed in order to meet the demand of job shop management flow. The job shop scheduling optimization strategy ensures that scheduling results can meet the actual production activities of job shop, and achieves a degree of reunification for work plan and actual production. Then the formal description of job shop scheduling problem and the optimization object for job shop scheduling optimization are given.Based on the traditional genetic algorithm, two efficient and feasible job shop scheduling statical algorithms have been provided to solve the intelligence problem of job shop scheduling optimization. First, an improved virus evolutionary genetic algorithm has been provided for minimizing the maximal completion time; second, an integer coded partheno genetic algorithm has been provided for minimizing the average flow time. Both algorithms are good at convergence rate and optimum solution, and meet the multi-objective requirements on job shop scheduling problems.Based on uncertain random events in the production of the single and small batch enterprise, a job shop scheduling dynamic algorithm by considering uncertain factors has been provided to solve the agility problem of job shop scheduling optimization. It can control product progress and adjust the plan to meet the dynamic randomness need of job shop scheduling. Then the driving mechanism combining event-driven with cycle-driven has been proposed to adapt the environment change during job shop production and to increase stability of MES.A single and small batch MES has been designed and developed based on the architecture and the optimization method proposed in this thesis, and the job shop scheduling algorithms have been implemented and embedded into MES. According to the job shop scheduling practical application problems, the architecture of single and small batch MES and its job shop scheduling optimization method have been validated.