Experimental Study of Surface Roughness of Pine Wood by High-Speed Milling

The surface roughness of wood has a great influence on its performance and is very important indicator in processing manufacturing. In this paper, we use the central composite design experiment (CCD experiment) artificial neural network (ANN) model to study changing pattern during high-speed milling process pine wood. CCD experiments, spindle speed, feed depth cut are used as influencing factors, index analyze variation law fit parameter equation. By measuring chip size each group experiment, ANN predict under machining by test group. experimental results showed that mean error prediction values (12.2%) was larger than (7.8%), squared (MSE) 0.025, absolute percentage error(MAPE) 0.01, coefficient determination R2 0.95. Compared with had higher accuracy. paper can provide some guidance for processing.