Prediction of Surface Characteristics of Cut Surfaces Produced by Plasma Arc Cutting Process by Using Image Processing and Fuzzy Logic Technique

Abstract

Plasma arc cutting process is one of the advanced nonconventional machining processes which is frequently used in modern metal cutting industries to compete with the laser cutting process. To obtain better surface quality during the plasma arc cutting process is one of the challenging issues. The controlling parameters such as cutting speed, gas flowrate, and arc current are the most influencing parameters which affect the surface roughness of the machined material. In this research, the fuzzy logic along with image processing is used to predict the surface roughness (Ra) of square plates machined by the plasma arc cutting process. The process parameters considered for the experiments were cutting speed (CS), gas flow rate (GFR), and arc current (C). Response Surface Methodology (RSM) was used to design the experimental runs and a total of 15 sets of experiments were performed and responses were measured. Fuzzy rule-based modeling can be effectively used to predict the surface roughness. Experimental results were compared with the predicted values. Base on the study it was observed that experimental results have got in good agreement with predicted results.