基于Plant Simulation的柴油机缸体生产线仿真与配置优化
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摘要
针对某柴油机缸体生产线设备利用率不足和生产效率低的问题,借助Plant Simulation软件建立该生产线的仿真模型,分析生产线的运行情况,并获得生产线设备利用率、生产率等信息。然后,利用遗传算法,对各个缓冲区的容量进行优化。最后,根据仿真结果与生产线实际状况,采用在第一、第二瓶颈工序分别配置容量为19和3的缓冲区,并安排线外机床定期清理缓冲区积压工件的优化方案。研究结果表明,所提出的优化方案可以将设备的平均利用率和生产线的生产率分别提高3. 4%和9. 4%。该研究可以为优化生产线提供指导,减少企业资源的浪费。
To solve the problem of insufficient utilization and production efficiency of a diesel engine cylinder block production line,a simulation model was established based on Plant Simulation. Firstly,the operation of the production line was analyzed and the related information was obtained. Secondly,the capacity of each buffer was optimized using genetic algorithm( GA). At last,according to the simulation results and the actual situation of the production line,an improvement scheme was proposed that the buffer was configured for the first and second bottlenecks with corresponding capacity 19 and 3,and an off-line machine tool was arranged to clean up the buffer backlog regularly. The results indicate that the average utilization rate of equipment was increased by 3. 4% and productivity by 9. 4%. This research can reduce the waste of enterprise resources and provide guidance for the adjustment of production lines.
To solve the problem of insufficient utilization and production efficiency of a diesel engine cylinder block production line,a simulation model was established based on Plant Simulation. Firstly,the operation of the production line was analyzed and the related information was obtained. Secondly,the capacity of each buffer was optimized using genetic algorithm( GA). At last,according to the simulation results and the actual situation of the production line,an improvement scheme was proposed that the buffer was configured for the first and second bottlenecks with corresponding capacity 19 and 3,and an off-line machine tool was arranged to clean up the buffer backlog regularly. The results indicate that the average utilization rate of equipment was increased by 3. 4% and productivity by 9. 4%. This research can reduce the waste of enterprise resources and provide guidance for the adjustment of production lines.
引文
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[13]Silva M F,Reis C,Pimenta R. Development of an application for balancing product flow lines through genetic algorithms[J]. International Journal of Business Excellence,2016,9(3):310-331.
[14]王凌,张亮.有限缓冲区流水线调度的多搜索模式遗传算法[J].计算机集成制造系统,2005,11(7):1041-1046.
[2]徐文杰,綦法群,冯德贵.基于整流化的生产线精益改善方法研究[J].制造技术与机床,2015(2):131-135.
[3]李翔,陈庆新,俞爱林,等.基于排队网模型的柔性流水车间缓冲区容量优化[J].计算机集成制造系统,2016,22(10):2348-2354.
[4]Ham W K,Chong M K,Sang C P. Template-based variant process planning for manned assembly lines[J]. International Journal of Computer Integrated Manufacturing,2016,30(9):1-12.
[5]陈国辉,鄢烈祥,史彬. Modeling and optimization for short-term scheduling of multipurpose batch plants[J].中国化学工程学报:英文版,2014,22(6):682-689.
[6]吴晟,赵湘莲. D公司生产线平衡问题实证研究[J].制造技术与机床,2017(1):153-156.
[7]Song L,Jin S,Tang P. Simulation and optimization of logistics distribution for an engine production line[J]. Journal of Industrial Engineering&Management,2016,9(1):59-72.
[8]刘明周,王小巧,张铭鑫,等.不确定环境下混流装配线动态准时制物料配送系统[J].计算机集成制造系统,2014,20(12):3020-3031.
[9]Jahangirian M,Eldabib T,Stergioulas L K,et al. Simulation in manufacturing and business:a review[J]. European Journal of Operational Research,2010,203(1):1-13.
[10]Ni J F,Tang K Z. Simulation andoptimization of job shop scheduling for dry transformers based on e M-Plant[J]. Applied Mechanics&Materials,2010,43:382-386.
[11]Yegul M F,Erenay F S,Striepe S,et al. Improving configuration of complex production lines via simulation-based optimization[J]. Computers&Industrial Engineering,2017,109:295-312.
[12]周金平.生产系统仿真:Plant Simulation应用教程[M].北京:电子工业出版社,2011.
[13]Silva M F,Reis C,Pimenta R. Development of an application for balancing product flow lines through genetic algorithms[J]. International Journal of Business Excellence,2016,9(3):310-331.
[14]王凌,张亮.有限缓冲区流水线调度的多搜索模式遗传算法[J].计算机集成制造系统,2005,11(7):1041-1046.