naa a22 4500 510822967 CHVBK 20180411083542.0 cr unu---uuuuu 180411e20131201xx s 000 0 eng 10.1007/s12541-013-0284-7 doi (NATIONALLICENCE)springer-10.1007/s12541-013-0284-7 Pressure path optimization of hydrodynamic deep drawing of cylindrical-conical parts [Elektronische Daten] [Amirreza Yaghoobi, Hamid Baseri, Mohammad Bakhshi-Jooybari, Abdolhamid Gorji] Pressure path is one of the most important parameters in hydrodynamic deep drawing process which affect on thickness distribution and bursting in the parts. In this study, a combination of finite element simulation and artificial intelligence was used to optimize the pressure path in hydrodynamic deep drawing process of cylindrical-conical parts to reach the minimum thickness reduction in critical region of product. First, a finite element simulation model was verified based on experimental results. Then, a neural network model was developed using the data generated from the verified finite element model to predict the thickness in critical region of product. The results indicated that the neural network model can be applied successfully for prediction of sheet thickness. In addition, the neural network model was used as a function in simulated annealing algorithm to maximize the thickness in the mentioned critical region. The final results showed that utilization of the optimized loading path yields good uniform thickness distribution of the part. Korean Society for Precision Engineering and Springer-Verlag Berlin Heidelberg, 2013 Pressure path nationallicence Hydrodynamic nationallicence Deep drawing nationallicence Neural network nationallicence Simulated annealing nationallicence Optimization nationallicence Yaghoobi Amirreza Mechanical Engineering Department, Babol University of Technology, Shariati avenue, POBox 484, Babol, Iran aut Baseri Hamid Mechanical Engineering Department, Babol University of Technology, Shariati avenue, POBox 484, Babol, Iran aut Bakhshi-Jooybari Mohammad Mechanical Engineering Department, Babol University of Technology, Shariati avenue, POBox 484, Babol, Iran aut Gorji Abdolhamid Mechanical Engineering Department, Babol University of Technology, Shariati avenue, POBox 484, Babol, Iran aut International Journal of Precision Engineering and Manufacturing Springer Berlin Heidelberg 14/12(2013-12-01), 2095-2100 2234-7593 14:12<2095 2013 14 12541 https://doi.org/10.1007/s12541-013-0284-7 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s12541-013-0284-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Yaghoobi Amirreza Mechanical Engineering Department, Babol University of Technology, Shariati avenue, POBox 484, Babol, Iran aut NATIONALLICENCE 700 1- Baseri Hamid Mechanical Engineering Department, Babol University of Technology, Shariati avenue, POBox 484, Babol, Iran aut NATIONALLICENCE 700 1- Bakhshi-Jooybari Mohammad Mechanical Engineering Department, Babol University of Technology, Shariati avenue, POBox 484, Babol, Iran aut NATIONALLICENCE 700 1- Gorji Abdolhamid Mechanical Engineering Department, Babol University of Technology, Shariati avenue, POBox 484, Babol, Iran aut NATIONALLICENCE 773 0- International Journal of Precision Engineering and Manufacturing Springer Berlin Heidelberg 14/12(2013-12-01), 2095-2100 2234-7593 14:12<2095 2013 14 12541 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer