Journal of Emerging Trends in Engineering and Applied Sciences: Research Areas

Article Title: Prediction and Optimisation of Surface Roughness in Face Milling Operation Using Regression and Fuzzy Logic Approach
by Anil Antony Sequeira

Abstract:
Surface finish is important objective function in manufacture engineering. The surface quality in face milling process depends on several factors such as rotational speed of the cutter, feed rate, depth of cut, etc. Hence high standard cutting conditions are need to be introduced using statistical models or the artificial-intelligence-based models to find proper surface finish. This research work aims at the prediction of the surface roughness in face milling operation by using linear regression model and fuzzy logic approach. Finding the optimal surface roughness depending upon the predicted results. And comparison of results obtained from linear regression model and fuzzy logic approach and to suggest the best model in prediction and optimization of surface roughness in face milling. From the findings it is found that the fuzzy model gives better closest value as compared to linear regression model. Thus the fuzzy environment is selected for predictions and optimization of surface roughness. Further this approach can be used for predictions and optimization of surface roughness along with cutting forces for generating adaptive control system for CNC machines.

Keywords: surface roughness, face milling, linear regression, fuzzy logic, taguchi method

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