随着定制化生产的市场需求日趋显著,Seru生产系统(seru production system,SPS)应运而生,并逐渐成为生产研究领域的热点。文章针对混合Seru生产系统的构建以及调度问题进行研究,即在短生产线生产场景下,基于巡回式Seru单元,建立混合Ser...随着定制化生产的市场需求日趋显著,Seru生产系统(seru production system,SPS)应运而生,并逐渐成为生产研究领域的热点。文章针对混合Seru生产系统的构建以及调度问题进行研究,即在短生产线生产场景下,基于巡回式Seru单元,建立混合Seru生产系统的数学模型,并以最大完工时间以及总工时建立双优化目标,决策混合Seru的构建顺序。先基于黏菌优化算法,针对其初始化效率低的局限性,引入Tent混沌映射以及精英反向学习策略,得到混沌精英黏菌(chaoticeliteslimemouldalgorithm,CESMA)算法。最后,通过实验,验证了混合Seru生产系统中,混沌精英黏菌算法对于混合Seru生产系统构建实例的优越性。展开更多
赛汝(SE RU)生产是源于日本电子装配制造企业生产现场的新型生产管理方式,可解决多品种小批量、变品种变批量市场环境下流水线方式的柔性不足和丰田生产方式的低效率问题,已在佳能、索尼等日本电子装配企业广泛采用并取得很好的效果,也...赛汝(SE RU)生产是源于日本电子装配制造企业生产现场的新型生产管理方式,可解决多品种小批量、变品种变批量市场环境下流水线方式的柔性不足和丰田生产方式的低效率问题,已在佳能、索尼等日本电子装配企业广泛采用并取得很好的效果,也因此引起了学术界的广泛关注和研究。本文在分析赛汝生产方式的产生背景与特点的基础上,从理论上多维度比较分析了赛汝生产与流水线生产、单元制造和丰田生产方式的本质区别和优势。构建随机环境下SERU系统性能的评价指标,包括效率指标、成本指标和稳定性指标;基于A R E NA的仿真比较分析系统,从计算仿真的角度在统计意义上比较分析赛汝生产方式与流水线方式在产品波动型、批量波动型、共同波动型场景下的性能指标。研究发现SERU生产方式比流水生产方式在生产效率、生产成本和稳定性方面均有较大的提升,生产效率明显提升。展开更多
This paper investigates the production scheduling problems of allocating resources and sequencing jobs in the seru production system(SPS).As a new-type manufacturing mode arising from Japanese production practices,ser...This paper investigates the production scheduling problems of allocating resources and sequencing jobs in the seru production system(SPS).As a new-type manufacturing mode arising from Japanese production practices,seru production can achieve efficiency,flexibility,and responsiveness simultaneously.The production environment in which a set of jobs must be scheduled over a set of serus according to due date and different execution modes is considered,and a combination optimization model is provided.Motivated by the problem complexity and the characteristics of the proposed seru scheduling model,a nested partitioning method(NPM)is designed as the solution approach.Finally,computational studies are conducted,and the practicability of the proposed seru scheduling model is proven.Moreover,the efficiency of the nested partitioning solution method is demonstrated by the computational results obtained from different scenarios,and the good scalability of the proposed approach is proven via comparative analysis.展开更多
文摘随着定制化生产的市场需求日趋显著,Seru生产系统(seru production system,SPS)应运而生,并逐渐成为生产研究领域的热点。文章针对混合Seru生产系统的构建以及调度问题进行研究,即在短生产线生产场景下,基于巡回式Seru单元,建立混合Seru生产系统的数学模型,并以最大完工时间以及总工时建立双优化目标,决策混合Seru的构建顺序。先基于黏菌优化算法,针对其初始化效率低的局限性,引入Tent混沌映射以及精英反向学习策略,得到混沌精英黏菌(chaoticeliteslimemouldalgorithm,CESMA)算法。最后,通过实验,验证了混合Seru生产系统中,混沌精英黏菌算法对于混合Seru生产系统构建实例的优越性。
文摘赛汝(SE RU)生产是源于日本电子装配制造企业生产现场的新型生产管理方式,可解决多品种小批量、变品种变批量市场环境下流水线方式的柔性不足和丰田生产方式的低效率问题,已在佳能、索尼等日本电子装配企业广泛采用并取得很好的效果,也因此引起了学术界的广泛关注和研究。本文在分析赛汝生产方式的产生背景与特点的基础上,从理论上多维度比较分析了赛汝生产与流水线生产、单元制造和丰田生产方式的本质区别和优势。构建随机环境下SERU系统性能的评价指标,包括效率指标、成本指标和稳定性指标;基于A R E NA的仿真比较分析系统,从计算仿真的角度在统计意义上比较分析赛汝生产方式与流水线方式在产品波动型、批量波动型、共同波动型场景下的性能指标。研究发现SERU生产方式比流水生产方式在生产效率、生产成本和稳定性方面均有较大的提升,生产效率明显提升。
基金This research was sponsored by National Natural Science Foundation of China(Grant No.71401075,71801129)the Fundamental Research Funds for the Central Universities(No.30922011406)+1 种基金System Science and Enterprise Development Research Center(Grant No.Xq22B06)Grant-in-Aid for Scientific Research(C)of Japan(Grant No.20K01897).
文摘This paper investigates the production scheduling problems of allocating resources and sequencing jobs in the seru production system(SPS).As a new-type manufacturing mode arising from Japanese production practices,seru production can achieve efficiency,flexibility,and responsiveness simultaneously.The production environment in which a set of jobs must be scheduled over a set of serus according to due date and different execution modes is considered,and a combination optimization model is provided.Motivated by the problem complexity and the characteristics of the proposed seru scheduling model,a nested partitioning method(NPM)is designed as the solution approach.Finally,computational studies are conducted,and the practicability of the proposed seru scheduling model is proven.Moreover,the efficiency of the nested partitioning solution method is demonstrated by the computational results obtained from different scenarios,and the good scalability of the proposed approach is proven via comparative analysis.
