A review of machining parameters’ influence on surface roughness

Abstract

Manufacturing is essential for modern economics, and machining processes are integral to achieve high quality without forgetting productivity and sustainability in machined components. Surface roughness formed during machining influences the functionality, longevity, reliability, and efficiency of produced parts. Industries like aerospace, medical, and nuclear require high performance components and therefore a more stringent control of surface roughness of machine parts. This study explores the effects of machining process parameters and tool geometry on surface finish. Although, the surface roughness increases with the increasing feed rate and decreases with the increasing cutting speed, the combined interplay between these parameters is highly complex and non-linear. Additionally, increasing the tool nose radius improves the surface roughness. This study develops an ANN model for improving the prediction accuracy of surface roughness at different process conditions. The developed model predicted the surface roughness with an accuracy of nearly 84% and additionally also captured the non-linearity in the machining process efficiently. Furthermore, the accuracy can be improved by employing a hybrid FE-Exp approach to increase the training dataset.