Prediction of Surface Roughness in End Milling with Gene Expression Programming

Surface roughness has a great influence on the functional properties of the product. Finding the rules that how process factors and environment factors affect the values of surface roughness will help to set the process parameters of the future and then improve production quality and efficiency. Since surface roughness is impacted by different machining parameters and the inherent uncertainties in the machining process, how to predict the surface roughness becomes a challengeable problem for the researchers and engineers. In this paper, a method based on gene expression programming (GEP) has been proposed to construct the prediction model of surface roughness. GEP combines the advantages of the genetic algorithm (GA) and genetic programming (GP). By considering GEP as a very successful technique for function mining and formula found, it should be suitable to solve the above problem. On the basis of defining a GEP environment for the problem and improving the method of creating constant, the explicit prediction model of surface roughness can been constructed. To verify the feasibility and performance of the proposed approach, experimental studies conducted to compare this approach with some previous works are presented. The experimental results show that the proposed approach has achieved satisfactory improvement and obtained good results for several widespread studied problems.