A Strategy for the Compensation of Errors in Five-Axis Machining

This paper outlines a strategy for error compensation in five-axis machining. The strategy uses a neural network model for compensation of errors due to changes in temperature and axis motion. Long term errors due to wear will be addressed with an adaptive approach. A method based on the analysis of the neural network weights is used for selecting the most relevant thermocouple inputs. Preliminary results show the strategy to be capable of …