基于Witness的机载薄壁类光电组件装配生产线仿真与优化
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摘要
传统的薄壁类光电组件产品由单名工人完成装配,生产效率低,产品质量不稳定,为了解决这一难题,建立一条离散型生产线。文章基于实际数据建立生产线模型,利用Witness对其进行仿真,分析结果发现装配线存在不平衡和整体利用率过低的问题,然后根据分叉法得到装配生产线的优化方案,最后根据该方案建立新的仿真模型,再次利用Witness来验证优化方案,结果表明优化后方案较最初方案装配生产线效率提高29.5%。说明采用分叉法对装配线进行优化是可行的,有效的提高了薄壁类光电组件的生产率。
Thin-walled photovoltaic module are traditionally assembled by single worker. In order to solve the problem of low efficiency and unstable quality, a discrete production line is established. This production line model is setup based on the actual data, and Witness is used in the simulation of the model. Analysing the result finds that assembly line is not balanced and utilization rate is low. Then according to the Branch-Out method to get an optimized plan. Finally, a simulation model according to the optimized plan is built. Use Witness to verify the optimization scheme, and results show that efficiency increased by 29.5% compared with original assembly line. It shows that the Branch-Out method is feasible in improve the productivity of thin-walled optoelectronic components to optimize the assembly line and effectively.
Thin-walled photovoltaic module are traditionally assembled by single worker. In order to solve the problem of low efficiency and unstable quality, a discrete production line is established. This production line model is setup based on the actual data, and Witness is used in the simulation of the model. Analysing the result finds that assembly line is not balanced and utilization rate is low. Then according to the Branch-Out method to get an optimized plan. Finally, a simulation model according to the optimized plan is built. Use Witness to verify the optimization scheme, and results show that efficiency increased by 29.5% compared with original assembly line. It shows that the Branch-Out method is feasible in improve the productivity of thin-walled optoelectronic components to optimize the assembly line and effectively.
引文
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[10] Andrey K,Vitaly D,Alexey P,et al.Simulation modeling of assembly processes in digital manufacturing[J].Procedia CIRP,2018,67 :470-475.
[2] 茹奕,于龙振,王志宪.进气歧管装配生产线的Witness仿真与优化[J].组合机床与自动化加工技术,2017(11):126-129,133.
[3] 李琴,刘海东.某生产系统基于Witness的仿真与优化[J].现代制造工程,2016(9):91-95.
[4] 宁方华,周晓敏.基于多节点控制的柔性生产线缓冲容量建模与Witness仿真[J].浙江理工大学学报,2015,33(1):62-66.
[5] 杜鹏程.基于仿真的汽车车身装配线的平衡与优化研究[D].郑州:中原工学院,2015.
[6] 余珂.基于仿真的汽车零部件多品多阶供应链网络建模与优化[D].杭州:浙江大学,2017.
[7] 龚立雄,黄敏,宋李俊,等.Witness在摩托车油箱涂装生产线系统中的仿真应用[J].物流技术,2014,33(17):404-406.
[8] 崔华春,尹纯建,贾焜,等.基于实体流程图和Witness仿真的航空货运离港系统仿真分析与优化研究[J].物流科技,2016,39(10):83-89.
[9] Manns M,Wallis A,Deuse J.Automatic Proposal of Assembly Work Plans with a Controlled Natural Language[J].Procedia CIRP,2015,33 :345-350.
[10] Andrey K,Vitaly D,Alexey P,et al.Simulation modeling of assembly processes in digital manufacturing[J].Procedia CIRP,2018,67 :470-475.