An ANN Approach to Determine the Surface Roughness in End Milling Cutter
Shrishail B. Sollapur, Prasanna Raut, Devakant Baviskar, Dr Mahesh M Kawade
Abstract
Surface finish is an important indication in the manufacturing process, particularly during milling processes.The goal of this project is to predict surface roughness using artificial neural networks.The neural network model efficiently determines the ideal cutting parameter values for various milling settings, resulting in reduced surface roughness.The current study is an experimental inquiry into end milling of M.S material using a carbide tool, examining the effect of various cutting settings on surface roughness.Using an artificial neural network (ANN), the study creates a link between surface roughness and cutting input parameters such spindle speed, feed, and depth of cut.The findings of this study have practical implications for industrial application, providing a way to minimise the time and expenses involved with surface roughness prediction.