Empirical Modeling for Surface Roughness of Turning using A Recently Emerged Evolutionary Approach
Keywords:
Surface roughness, turning, genetic programming, evolutionary processAbstract
Prediction of surface roughness is essential in any machining process as it plays a vital role in determining the quality of components. A good quality surface improves fatigue strength, wear resistance, and corrosion resistance. The present work involves the development of a mathematical model for surface roughness of a turning process based on a recently emerged evolutionary approach called Genetic programming (GP). The machining parameters of turning such as cutting speed, feed rate, and nose radius are considered as the input variables. Two sets of experimental data were taken: training data set and testing data set. The model established by GP based on the training data set is validated with the testing data set.
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