带新订单插入的虚拟制造单元重构方法研究OACHSSCDCSTPCD
A Virtual Manufacturing Cell Reconfiguration Method with New Order Insertion
虚拟制造单元旨在更改物流走向和优化制造单元,提高车间生产效率和物流柔性,广泛存在于多品种小批量生产车间.随着新订单插入,产品类型与工艺路径不断变化,原有虚拟制造单元易引起设备负载不均衡和生产效率下降.针对新订单插入情形,引入连续相同工序,设计一种新的衡量新订单与原有虚拟制造单元的相似度指标;针对虚拟制造单元重构情形,建立以设备负载均衡、总运输成本、跨单元次数和单元继承率为优化目标的虚拟制造单元重构数学模型.另外,对基于分解的多目标进化算法(multi-objective evolutionary algorithm based on decom-position,MOEA/D)进行改进,采用多种交叉算子提高全局搜索效率,采用基于模拟退火的邻域搜索提高局部探寻能力.最后,以某企业机加工车间实际案例和 10组标杆案例,验证了所提方法的有效性和卓越性,为虚拟制造单元重构决策提供理论参考依据.
Virtual manufacturing cells is designed to modify logistics routes and optimize manufacturing cells,enhancing workshop production efficiency and logistical flexibility.They are widely used in multi-variety and small-batch production workshops.With new order insertion,changes in product types and process paths can lead to imbalances in equipment load and decreased production efficiency within original virtual manufacturing cells.To address this issue,a new indicator to measure the similarity between new orders and original virtual manufacturing cells is introduced,incorporating continuous identical operations.A mathematical model for virtual manufacturing cell reconfiguration is established with the objectives of equipment load balancing,total transportation cost,number of inter-cell movements,and cell inheritance rate.In addition,an improved multi-objective evolutionary algorithm based on decomposition(MOEA/D)is proposed,which utilizes multiple crossover operators to improve global search efficiency and adopts a simulated annealing-based neighborhood search to enhance local exploration capability.Finally,the effectiveness and excellence of the proposed method are verified by using an actual case from the machining workshop in a factory and 10 benchmark cases,providing theoretical references for decisions of virtual manufacturing cell reconfiguration.
张利平;龚雨成
武汉科技大学机械自动化学院,湖北 武汉 430081武汉科技大学冶金装备及其控制教育部重点实验室,湖北 武汉 430081
经济学
虚拟制造单元单元重构多目标优化改进MOEA/D算法新订单插入
virtual manufacturing cellcell reconfigurationmulti-objective optimizationimproveed MOEA/Dnew order insertion
《工业工程》 2024 (6)
103-114,12
国家自然科学基金资助项目(51875420)
评论