{"title":"应用人工神经网络(ANN)优化IS2062 HR钢板料冲裁间隙的实验研究","authors":"Vijaya P.Patil, Pradip P.Patil, Nilesh E. Ingale","doi":"10.1109/IEMECONX.2019.8876992","DOIUrl":null,"url":null,"abstract":"In sheet metal forming, particularly in sheet metal blanking, an unsuitable value of clearance may lead to secondary crack formation. Cracks lead to uneven edges leading to loss of productivity in terms of quality of surface finish and dimensional accuracy. In the present work, experiments are carried out on the power press with the uni-punch tool as a cutting tool and IS2062HR material. In blanking, punch penetration is varied to find a depth at which crack initiates in sheet metal. After punching, shear angle and fracture angle and punch penetration considered as input parameters from the available ranges. Experimentally, the optimum value of clearance obtained by plotting angles versus per cent clearance. The input values fed to train the Neural Network (NN) which predicts clearance for different unknown input parameters. The results of predictions are well within the range of experimental values. However, the material ductility influences the clearance selection for blanking.","PeriodicalId":358845,"journal":{"name":"2019 9th Annual Information Technology, Electromechanical Engineering and Microelectronics Conference (IEMECON)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Experimental Investigations of Optimum Sheet Metal Blanking Clearance for IS2062 HR Steel Using Artificial Neural Network(ANN)\",\"authors\":\"Vijaya P.Patil, Pradip P.Patil, Nilesh E. Ingale\",\"doi\":\"10.1109/IEMECONX.2019.8876992\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In sheet metal forming, particularly in sheet metal blanking, an unsuitable value of clearance may lead to secondary crack formation. Cracks lead to uneven edges leading to loss of productivity in terms of quality of surface finish and dimensional accuracy. In the present work, experiments are carried out on the power press with the uni-punch tool as a cutting tool and IS2062HR material. In blanking, punch penetration is varied to find a depth at which crack initiates in sheet metal. After punching, shear angle and fracture angle and punch penetration considered as input parameters from the available ranges. Experimentally, the optimum value of clearance obtained by plotting angles versus per cent clearance. The input values fed to train the Neural Network (NN) which predicts clearance for different unknown input parameters. The results of predictions are well within the range of experimental values. However, the material ductility influences the clearance selection for blanking.\",\"PeriodicalId\":358845,\"journal\":{\"name\":\"2019 9th Annual Information Technology, Electromechanical Engineering and Microelectronics Conference (IEMECON)\",\"volume\":\"98 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 9th Annual Information Technology, Electromechanical Engineering and Microelectronics Conference (IEMECON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEMECONX.2019.8876992\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 9th Annual Information Technology, Electromechanical Engineering and Microelectronics Conference (IEMECON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEMECONX.2019.8876992","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Experimental Investigations of Optimum Sheet Metal Blanking Clearance for IS2062 HR Steel Using Artificial Neural Network(ANN)
In sheet metal forming, particularly in sheet metal blanking, an unsuitable value of clearance may lead to secondary crack formation. Cracks lead to uneven edges leading to loss of productivity in terms of quality of surface finish and dimensional accuracy. In the present work, experiments are carried out on the power press with the uni-punch tool as a cutting tool and IS2062HR material. In blanking, punch penetration is varied to find a depth at which crack initiates in sheet metal. After punching, shear angle and fracture angle and punch penetration considered as input parameters from the available ranges. Experimentally, the optimum value of clearance obtained by plotting angles versus per cent clearance. The input values fed to train the Neural Network (NN) which predicts clearance for different unknown input parameters. The results of predictions are well within the range of experimental values. However, the material ductility influences the clearance selection for blanking.