Modelling and analysing the cutting forces in high speed hard end milling using neural network

• Main Authors: Al Hazza, Muataz Hazza Faizi, Adesta, Erry Yulian Triblas
• Format: Article
• Language: English
• Published: Asian Research Publishing Network (ARPN) 2015
• Subjects: T Technology (General)
• Online Access: http://irep.iium.edu.my/46572/1/jeas_1215_3162.pdf; http://irep.iium.edu.my/46572/; http://www.arpnjournals.org/jeas/research_papers/rp_2015/jeas_1215_3162.pdf

High speed hard end milling is one of complex and costly shape machining compared to other machining processes. In high speed end hard milling, the tool wear or breakage are mostly happened due to the cutting forces which lead. In this research, the influencing of cutting speed, feed rate and depth of cut on cutting forces have been analysed and modelled using the artificial neural network approach using experimental data. The experiment was conducted using high speed end milling of AISI D2 cold work tool steel material hardened to 52 HRC under dry cutting condition. The measured data have been used to train and validate the outputs. The artificial neural network (ANN) has been used for modeling and predicting the cutting forces using the JMP software. The new model shows high accuracy compared the measured forces.