云制造是制造业在云计算支撑下的一种新的商务模式,其研究现处于探索和初步实践阶段。在Lenk方法基础上,从制造业信息化现状和发展需求出发,构建了商务云制造栈模型,其中包括资源即服务模型(Resource as a Service,Raa S)、基础设施即...云制造是制造业在云计算支撑下的一种新的商务模式,其研究现处于探索和初步实践阶段。在Lenk方法基础上,从制造业信息化现状和发展需求出发,构建了商务云制造栈模型,其中包括资源即服务模型(Resource as a Service,Raa S)、基础设施即服务模型(Infrastructure as a Service,Iaa S)、平台即服务模型(Platform as a Service,Paa S)、软件即服务模型(Software as a Service,Saa S)及人力资源即服务模型(Human as a Service,Haa S)这五层结构,并对制造资源虚拟化、云端数据管理、制造资源调度以及云端信息安全等云制造关键技术进行了分析。在某集团信息化改造项目中,将该云制造栈模型运用到集团私有云的网络环境搭建中,并开发了基于Saa S的应用系统。展开更多
Aiming at the flexible manufacturing system with multi-machining and multi-assembly equipment, a new scheduling algorithm is proposed to decompose the assembly structure of the products, thus obtaining simple scheduli...Aiming at the flexible manufacturing system with multi-machining and multi-assembly equipment, a new scheduling algorithm is proposed to decompose the assembly structure of the products, thus obtaining simple scheduling problems and forming the cOrrespOnding agents. Then, the importance and the restriction of each agent are cOnsidered, to obtain an order of simple scheduling problems based on the cooperation game theory. With this order, the scheduling of sub-questions is implemented in term of rules, and the almost optimal scheduling results for meeting the restriction can be obtained. Experimental results verify the effectiveness of the proposed scheduling algorithm.展开更多
An improved ant colony optimization （ACO） algorithm is utilized in cell scheduling of the flexible manufaturing process for considering the instrument constraint, manufacturing cost and time. Firstly, the initial we...An improved ant colony optimization （ACO） algorithm is utilized in cell scheduling of the flexible manufaturing process for considering the instrument constraint, manufacturing cost and time. Firstly, the initial weighted directional diagram is set up. Secondly, the algorithm based on the dynamic pheromone updating ensures the quick convergence and the optimal solution, thus improving the feasibility and the stability of the schedule system. Aiming at reducing collaboration with external partners, decreasing the total cost and balancing the production process, the algorithm is efficient in supporting the management process of the manufacturing cell and in strengthening the information arrangement capabitity of the scheduling system. Finally, experimental results of the improved algorithm are compared with those of other algorithms.展开更多
It is urgent to effectively improve the production efficiency in the running process of manufacturing systems through a new generation of information technology.According to the current growing trend of the internet o...It is urgent to effectively improve the production efficiency in the running process of manufacturing systems through a new generation of information technology.According to the current growing trend of the internet of things(IOT)in the manufacturing industry,aiming at the capacitor manufacturing plant,a multi-level architecture oriented to IOT-based manufacturing environment is established for a flexible flow-shop scheduling system.Next,according to multi-source manufacturing information driven in the manufacturing execution process,a scheduling optimization model based on the lot-streaming strategy is proposed under the framework.An improved distribution estimation algorithm is developed to obtain the optimal solution of the problem by balancing local search and global search.Finally,experiments are carried out and the results verify the feasibility and effectiveness of the proposed approach.展开更多
To improve the productivity of cluster tools in semiconductor fabrications,on the basis of stating scheduling problems,a try and error-based scheduling algorithm was proposed with residency time constraints and an obj...To improve the productivity of cluster tools in semiconductor fabrications,on the basis of stating scheduling problems,a try and error-based scheduling algorithm was proposed with residency time constraints and an objective of minimizing Makespan for the wafer jobs in cluster tools.Firstly,mathematical formulations of scheduling problems were presented by using assumptions and definitions of a scheduling domain.Resource conflicts were analyzed in the built scheduling model,and policies to solve resource conflicts were built.A scheduling algorithm was developed.Finally,the performances of the proposed algorithm were evaluated and compared with those of other methods by simulations.Experiment results indicate that the proposed algorithm is effective and practical in solving the scheduling problem of the cluster tools.展开更多
文摘云制造是制造业在云计算支撑下的一种新的商务模式,其研究现处于探索和初步实践阶段。在Lenk方法基础上,从制造业信息化现状和发展需求出发,构建了商务云制造栈模型,其中包括资源即服务模型(Resource as a Service,Raa S)、基础设施即服务模型(Infrastructure as a Service,Iaa S)、平台即服务模型(Platform as a Service,Paa S)、软件即服务模型(Software as a Service,Saa S)及人力资源即服务模型(Human as a Service,Haa S)这五层结构,并对制造资源虚拟化、云端数据管理、制造资源调度以及云端信息安全等云制造关键技术进行了分析。在某集团信息化改造项目中,将该云制造栈模型运用到集团私有云的网络环境搭建中,并开发了基于Saa S的应用系统。
文摘Aiming at the flexible manufacturing system with multi-machining and multi-assembly equipment, a new scheduling algorithm is proposed to decompose the assembly structure of the products, thus obtaining simple scheduling problems and forming the cOrrespOnding agents. Then, the importance and the restriction of each agent are cOnsidered, to obtain an order of simple scheduling problems based on the cooperation game theory. With this order, the scheduling of sub-questions is implemented in term of rules, and the almost optimal scheduling results for meeting the restriction can be obtained. Experimental results verify the effectiveness of the proposed scheduling algorithm.
文摘An improved ant colony optimization （ACO） algorithm is utilized in cell scheduling of the flexible manufaturing process for considering the instrument constraint, manufacturing cost and time. Firstly, the initial weighted directional diagram is set up. Secondly, the algorithm based on the dynamic pheromone updating ensures the quick convergence and the optimal solution, thus improving the feasibility and the stability of the schedule system. Aiming at reducing collaboration with external partners, decreasing the total cost and balancing the production process, the algorithm is efficient in supporting the management process of the manufacturing cell and in strengthening the information arrangement capabitity of the scheduling system. Finally, experimental results of the improved algorithm are compared with those of other algorithms.
基金supported by the National Natural Science Foundations of China(No. 51875171)
文摘It is urgent to effectively improve the production efficiency in the running process of manufacturing systems through a new generation of information technology.According to the current growing trend of the internet of things(IOT)in the manufacturing industry,aiming at the capacitor manufacturing plant,a multi-level architecture oriented to IOT-based manufacturing environment is established for a flexible flow-shop scheduling system.Next,according to multi-source manufacturing information driven in the manufacturing execution process,a scheduling optimization model based on the lot-streaming strategy is proposed under the framework.An improved distribution estimation algorithm is developed to obtain the optimal solution of the problem by balancing local search and global search.Finally,experiments are carried out and the results verify the feasibility and effectiveness of the proposed approach.
基金Projects(71071115,60574054) supported by the National Natural Science Foundation of China
文摘To improve the productivity of cluster tools in semiconductor fabrications,on the basis of stating scheduling problems,a try and error-based scheduling algorithm was proposed with residency time constraints and an objective of minimizing Makespan for the wafer jobs in cluster tools.Firstly,mathematical formulations of scheduling problems were presented by using assumptions and definitions of a scheduling domain.Resource conflicts were analyzed in the built scheduling model,and policies to solve resource conflicts were built.A scheduling algorithm was developed.Finally,the performances of the proposed algorithm were evaluated and compared with those of other methods by simulations.Experiment results indicate that the proposed algorithm is effective and practical in solving the scheduling problem of the cluster tools.
