Modeling of cutting forces in a face-milling operation with Gene Expression Programming

Cutting forces is one of the most fundamental elements that affect the performance of cutting operation. Finding the rules that how process and environment factors affect the values of cutting forces will help to set the process parameters of the future cutting operation and further improve production quality and efficiency. Since cutting forces is impacted by different machining parameters and the inherent uncertainties in the machining process, how to predict the cutting forces becomes a challengeable problem for the researchers and engineers. Gene Expression Programming (GEP) combines the advantages of the genetic algorithm (GA) and genetic programming (GP), and has been successfully applied in function mining and formula finding, so it should be suitable to solve the above problem. In this paper, a method based on GEP has been proposed to construct the prediction model of cutting forces in a face-milling operation. At the basis of defining a GEP environment for the problem and improving the method of constant creation, an explicit prediction model of cutting forces has been constructed. To verify the feasibility and performance of the proposed approach, experimental studies have been conducted to compare this approach with some previous works. The obtained results show that the constructed prediction model fits very well with the experimental data, and can be used to estimate the cutting forces and optimize the cutting parameters. The proposed method will lead to the reduction in production costs and production time, and improvement of product quality.