چکیده مقاله
Nowadays better production with minimum effort and lower cost is vital requirement of industrial production So all proved solutions in decreasing cost and enhancing quality has also close competition with each other Data mining and neural networks are both eminent methods in estimating the objective functions in manufacturing, so this research is aimed to develop an integrated methodology based on Finite Element Method FEM data mining in first part, FEM neural networks in the next to approximate the results of considered process parameters In this methodology, the FEM simulation is first used to create training cases for two mentioned algorithms, and the well trained algorithms Support Vector Machine in data mining method and Levenberg Marquardt in Neural Network method are used to predict the wall thickness Comparison between methods is done and data mining shows good accuracy but neural network shows better precision To validate the FEM results, related mold was made and FEM shows good conformity with experiment
کلیدواژهها
نویسندگان
P.M Kashtiban
Department of Mechanical Engineering, Urmia University of Technology, Urmia, Iran
J Tahmoresnezhad
Department of computer Engineering, Urmia University of Technology, Urmia, Iran
S Khalilpourazary
Department of Mechanical Engineering, Urmia University of Technology, Urmia, Iran
شیوه ارجاع
Kashtiban, P.M and Tahmoresnezhad, J and Khalilpourazary, S,1390,Deep Drawing Investigation Using Neural Network and Data Mining,12th Iranian Conference on Manufacturing Engineering (ICME 2010),Tehran
ارائهشده در
مجموعه مقالات دوازدهمین کنفرانس ملی مهندسی ساخت و تولید ایران6 دی 1390 · تهران