Study on the Cutting Prediction of Supercritical Material

Abstract

The technology of the artificial neural network (ANN) was applied in the research of supercritical material cutting. Two-dimensional Gaussian surfaces of the three cutting elements and workpiece surface hardness had been established fitting through JMP software. Base on the orthogonal milling experiments, the rules of cutting forces variation were forecasted, as well as the effect to the hardness on workpiece surface. The cutting parameters selected according to the process were built, providing an important basis for the optimization of machining conditions. The prediction results were in good agreement with the experimental results.

DOI: http://dx.doi.org/10.11591/telkomnika.v11i9.3265