This paper analyzes optimization algorithms of assembly time for a multi-head mounter. The algorithm in this paper is composed of four steps. First, it assigns the components to feeders based on the ＂one-to-many mapp...This paper analyzes optimization algorithms of assembly time for a multi-head mounter. The algorithm in this paper is composed of four steps. First, it assigns the components to feeders based on the ＂one-to-many mapping＂. Secondly, it assigns nozzles to heads by making full use of the ＂on-the-fly nozzle change＂ heads. Thirdly, it Qrganizes the feeder groups so that the heads can pick and place components group by group. Finally, it assigns feeder groups to slots. The result demonstrates that the algorithm has good performance in practice.展开更多
A chip mounter is the core equipment in the production line of the surface-mount technology,which is responsible for finishing the mount operation.It is the most complex and time-consuming stage in the production proc...A chip mounter is the core equipment in the production line of the surface-mount technology,which is responsible for finishing the mount operation.It is the most complex and time-consuming stage in the production process.Therefore,it is of great significance to optimize the load balance and mounting efficiency of the chip mounter and improve the mounting efficiency of the production line.In this study,according to the specific type of chip mounter in the actual production line of a company,a maximum and minimum model is established to minimize the maximum cycle time of the chip mounter in the production line.The production efficiency of the production line can be improved by optimizing the workload scheduling of each chip mounter.On this basis,a hybrid adaptive optimization algorithm is proposed to solve the load scheduling problem of the mounter.The hybrid algorithm is a hybrid of an adaptive genetic algorithm and the improved ant colony algorithm.It combines the advantages of the two algorithms and improves their global search ability and convergence speed.The experimental results show that the proposed hybrid optimization algorithm has a good optimization effect and convergence in the load scheduling problem of chip mounters.展开更多
基金This Project was supported by the special invite public bidding project of Key Equipment of Precision Manufacture of Guangdong Province of China (No. 20041A01).
文摘This paper analyzes optimization algorithms of assembly time for a multi-head mounter. The algorithm in this paper is composed of four steps. First, it assigns the components to feeders based on the ＂one-to-many mapping＂. Secondly, it assigns nozzles to heads by making full use of the ＂on-the-fly nozzle change＂ heads. Thirdly, it Qrganizes the feeder groups so that the heads can pick and place components group by group. Finally, it assigns feeder groups to slots. The result demonstrates that the algorithm has good performance in practice.
基金supported by the National Natural Science Foundation of China(Nos.U1911205,62073300,and 62076225)the National Key Research and Development Program of China(No.2021YFB3301602).
文摘A chip mounter is the core equipment in the production line of the surface-mount technology,which is responsible for finishing the mount operation.It is the most complex and time-consuming stage in the production process.Therefore,it is of great significance to optimize the load balance and mounting efficiency of the chip mounter and improve the mounting efficiency of the production line.In this study,according to the specific type of chip mounter in the actual production line of a company,a maximum and minimum model is established to minimize the maximum cycle time of the chip mounter in the production line.The production efficiency of the production line can be improved by optimizing the workload scheduling of each chip mounter.On this basis,a hybrid adaptive optimization algorithm is proposed to solve the load scheduling problem of the mounter.The hybrid algorithm is a hybrid of an adaptive genetic algorithm and the improved ant colony algorithm.It combines the advantages of the two algorithms and improves their global search ability and convergence speed.The experimental results show that the proposed hybrid optimization algorithm has a good optimization effect and convergence in the load scheduling problem of chip mounters.
