STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Mechatronics and Automation

Effect of Various Process Parameters on MRR in Manual Air Plasma Arc Cutting of AISI 1017 Mild Steel using ANN

  1. Pratishtha .
  2. C S Malvi

Abstract

As per recent industrial surveys it is investigated that manufacturing companies define the quality of thermal cutting process by the dimension of work material and cutting surface appearance. Therefore, the surface roughness and material removal rate (MRR) are primarily considered. In this work the effect of three input parameters air pressure (P), cutting current (I) and cutting velocity (v) on material removal rate (MRR) is obtained experimentally. An artificial neural network (ANN) model is also developed and trained by using experimental data. For developing ANN model, feed forward back propagation (FFBP) method is adopted with 3×n×1 architecture. The linear and tangent sigmoid transfer function at output and hidden layer are used.  The ANN model is validated by predicting accuracy. The model is also used to generate the contour plots which are helpful in identifying the optimal cutting region. The experimental work is carried out by using air plasma arc cutter KPT-4 by electra and with specimen of mild steel AISI 1017.

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