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作 者:杨磊 徐晓鸣 张海洋 曾伟镇 Yang Lei;Xu Xiaoming;Zhang Haiyang;Zeng Weizhen(School of Mechanical and Power Engineering,Guangdong Ocean University,Zhanjiang,Guangdong 524088,China;Little Talent Technology Company,Dongguan,Guangdong 523846,China)
机构地区:[1]广东海洋大学机械与动力工程学院,广东湛江524088 [2]小天才科技有限公司,广东东莞523846
出 处:《机电工程技术》2022年第5期170-173,共4页Mechanical & Electrical Engineering Technology
基 金:广东省教育厅青年创新人才类项目(编号:2016KQNCX059)。
摘 要:在市场竞争环境十分激烈的环境下,通过对生产线混流改造,来满足客户多样化的产品需求和降低企业生产成本的压力,而混流改造首先要解决的是混流生产线平衡问题。通过合并工艺相似的产品生产线,在考虑工序之间优先顺序、产品需求信息和作业时间约束下,以生产节拍和负荷均衡为目标,建立混流生产线第二类平衡问题的多目标混合整数规划模型,设计了双种群遗传算法,通过对A企业生产线混流改造和优化,生产节拍从77.35 s、77.35 s、60.26 s减少到48.16 s,生产率从53.1%、37.3%、50.9%提升至85.9%。研究结果表明混流改造以及双种群遗传算法能够有效地解决和改善第二类混流生产线平衡问题,减少了生产节拍以及提高生产平衡率,该方法和技术可以推广到其他类型的混流生产线设计与改造上。In the environment of fierce market competition,in order to meet the diversified product needs of customers and reduce production costs,it is necessary to carry out mixed-flow transformation of enterprise production lines.Mixed flow transformation must first solve the problem of mixed flow line balancing.By group technology,basing on relationship between the process,production demand information and operation time,multi-objective such as to minimize the cycle time and maximize load balancing were considered.A multi-objective mixed integer programming model for the second type of mixed flow production line balance problem was established.Then the double population genetic algorithm was used to solve it.Through the application of A company,the production cycle was reduced from 77.35 s,77.35 s,and 60.26 s to 48.16 s,and the productivity was increased from 53.1%,37.3%,and 50.9%to 85.9%.The results show that the mixed-flow transformation and two-population genetic algorithm can effectively solve and improve the second type of mixed-flow production line balance problem,reduce the production time and improve the production balance rate.The method and technology can be extended to other types of mixed-flow production line design and transformation.
分 类 号:TP391[自动化与计算机技术—计算机应用技术] TP27[自动化与计算机技术—计算机科学与技术]
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