چکیده مقاله
Hot machining is one of the most suitable methods for machining hard and super hard materials, which have high corrosive resistance and strength Affective factors in such machining are included as initial workpiece temperature and tool feed rate In this study, the hot machining process has been simulated The material of the workpiece was selected as AISI 1015 and corrected Coulomb low is used to model the friction effects between tool and chips Because determination of applied force over tool in simulation requires time and cost, artificial neural networks are used for this purpose Two parameters of initial workpiece temperature and tool feed rate, are considered as inputs of the neural network, while applied force on tool in X and Y directions are outputs To validate the simulation results, experimental results were compared with simulation results and an acceptable validation was gained
کلیدواژهها
نویسندگان
F. Azimi Far
Department of Mechanical Engineering, Islamic Azad university, majlesi branch, Iran
P. Foode
Department of Mechanical Engineering, Dehaghan Branch, Islamic Azad University, Dehaghan, Iran
شیوه ارجاع
Azimi Far, F. and Foode, P.,1390,Prediction of Hot Machining Force by Using Artificial Neural Network,12th Iranian Conference on Manufacturing Engineering (ICME 2010),Tehran
ارائهشده در
مجموعه مقالات دوازدهمین کنفرانس ملی مهندسی ساخت و تولید ایران6 دی 1390 · تهران