Improved CNC machining using NARMA neural systems

The NARMA (normal autoregressive moving average) neural network is based on the ARMA model used in time series analysis. NARMA networks can perform nonlinear analysis. It is shown that NARMA networks are capable of learning linear and nonlinear system dynamics. The networks are used to improve computer numerical control (CNC) machining precision. NARMA neural networks are used to learn the mapping between the actual workpiece dimensions and the commanded dimensions, including the effect of the change of stiffness of the workpiece during cutting. After training, the network then predicts the necessary corrective CNC commands which can reduce machining inaccuracies significantly. Computer simulations are performed showing that the machining precision is greatly improved compared to uncorrective cutting.<>