PRODUCTION SCHEDULING OPTIMIZATION OF FLEXIBLE MANUFACTURING SYSTEM FOR GREEN MANUFACTURING

The manufacturing industry is the economic pillar of the country, which can provide a large number of jobs and alleviate the employment pressure. In the manufacturing industry, the scheduling problem is the core problem of manufacturing intelligence and automation. Scheduling plays an extremely important role in the productivity as well as reliability of largescale complex production systems. Therefore, a production scheduling method based on a genetic algorithm is proposed, which first uses a genetic algorithm to achieve scheduling optimization. Then, the minimizing carbon emission method is introduced to achieve green manufacturing. Finally, the production scheduling system (PSS) of flexible manufacturing form is constructed. The experimental results show that the proposed production scheduling method has a better scheduling optimization effect. The resource utilization rate reaches 0.884, and the workpiece processing time is reduced to 0.32s. The carbon emission cost is significantly lower than that of the traditional production scheduling system. The results show that using genetic algorithms to optimize the production scheduling of flexible manufacturing systems is feasible. It can improve production efficiency while reducing carbon emissions. The model proposed in this study can be a good solution to practical problems in industrial production intelligence.