Title: Investigations on end-milling process by artificial neural network, finite element analysis and experimental studies
Authors: P. Palanisamy, I. Rajendran, S. Shanmugasundaram
Addresses: Department of Mechanical Engineering, Kumaraguru College of Technology, Coimbatore 641006, Tamilnadu, India. ' Department of Mechanical Engineering, Bannari Amman Institute of Technology, Sathyamangalam 638 401, Tamilnadu, India. ' Government College of Technology, Coimbatore 641013, Tamilnadu, India
Abstract: Chatter is a well known self excited-vibration between the tool and the workpiece. In this paper, Artificial Neural Network (ANN) has been used to predict the chatter-free vibrations Stability Lobe Diagram (SLD) for milling of AISI 1020 Steel, as it requires less computation time and is highly flexible. The occurrence of chatter for a particular combination of machining conditions is easily predicted using SLD plot. The SLD plot is validated using Fast Fourier Transform (FFT) analyser in a Universal Milling Machine. The results have shown a good agreement between chatter prediction and experimental values. The Nyquist Criterion is applied for studying the dynamic stability of the equivalent elastic system process. The result obtained from polar plots helps the designer to design the machine tool system having a minimum stiffness value of 4200 KN/mm in order to maintain the stability. Dynamic analysis has been performed using FEA to find the maximum deflection and stresses of cutter.
Keywords: end milling; cutting force; stability lobe diagram; artificial neural networks; ANNs; uncut chip thickness; finite element analysis; FEA; chatter vibration; steel; machine tool design; stiffness; cutter deflection; cutter stress; machining.
International Journal of Machining and Machinability of Materials, 2006 Vol.1 No.2, pp.233 - 257
Published online: 06 Oct 2006 *Full-text access for editors Access for subscribers Purchase this article Comment on this article