{"title":"基于粒子群算法的模具工艺优化","authors":"Huagang Liu, Zhixin Feng, Ruican Hao","doi":"10.1109/ICRIS.2017.64","DOIUrl":null,"url":null,"abstract":"The optimization of cutting parameters in the milling process of cutting tool is helpful to the quality control of the production process. Based on particle swarm optimization (PSO) algorithm, a method for optimizing the parameters of die casting process is presented. Based on the summary of the relative volume, the milling force and the deformation control parameters on the advantages of the traditional algorithm, using dichotomy iteration, respectively on the corner milling process for feed parameter optimization, and considering the three kinds of feed parameter optimization algorithms for rough machining, finish machining in machining efficiency and milling force limit the constraint conditions, select the maximum envelope parameters and minimum envelope curve feed for feeding after optimization. Finally, the particle swarm optimization algorithm is introduced into the optimization of the traditional optimization results, and the optimal feed quantity of two times is obtained. The simulation results show that the processing time is reduced by 32.6% after the optimization of the feed parameters of rough machining, and the maximum of milling force is always within the allowable range of the milling process.","PeriodicalId":443064,"journal":{"name":"2017 International Conference on Robots & Intelligent System (ICRIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization of Die Mold Process Based on Particle Swarm Optimization\",\"authors\":\"Huagang Liu, Zhixin Feng, Ruican Hao\",\"doi\":\"10.1109/ICRIS.2017.64\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The optimization of cutting parameters in the milling process of cutting tool is helpful to the quality control of the production process. Based on particle swarm optimization (PSO) algorithm, a method for optimizing the parameters of die casting process is presented. Based on the summary of the relative volume, the milling force and the deformation control parameters on the advantages of the traditional algorithm, using dichotomy iteration, respectively on the corner milling process for feed parameter optimization, and considering the three kinds of feed parameter optimization algorithms for rough machining, finish machining in machining efficiency and milling force limit the constraint conditions, select the maximum envelope parameters and minimum envelope curve feed for feeding after optimization. Finally, the particle swarm optimization algorithm is introduced into the optimization of the traditional optimization results, and the optimal feed quantity of two times is obtained. The simulation results show that the processing time is reduced by 32.6% after the optimization of the feed parameters of rough machining, and the maximum of milling force is always within the allowable range of the milling process.\",\"PeriodicalId\":443064,\"journal\":{\"name\":\"2017 International Conference on Robots & Intelligent System (ICRIS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Robots & Intelligent System (ICRIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICRIS.2017.64\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Robots & Intelligent System (ICRIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICRIS.2017.64","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimization of Die Mold Process Based on Particle Swarm Optimization
The optimization of cutting parameters in the milling process of cutting tool is helpful to the quality control of the production process. Based on particle swarm optimization (PSO) algorithm, a method for optimizing the parameters of die casting process is presented. Based on the summary of the relative volume, the milling force and the deformation control parameters on the advantages of the traditional algorithm, using dichotomy iteration, respectively on the corner milling process for feed parameter optimization, and considering the three kinds of feed parameter optimization algorithms for rough machining, finish machining in machining efficiency and milling force limit the constraint conditions, select the maximum envelope parameters and minimum envelope curve feed for feeding after optimization. Finally, the particle swarm optimization algorithm is introduced into the optimization of the traditional optimization results, and the optimal feed quantity of two times is obtained. The simulation results show that the processing time is reduced by 32.6% after the optimization of the feed parameters of rough machining, and the maximum of milling force is always within the allowable range of the milling process.