A New Tool Wear Modeling Method Based on Project Pursuit Regression

Abstract

Tool wear is a major contributor to the dimensional errors of a workpiece in precision machining. Tool wear modeling is an effective way to predict the tool wear loss in milling process. In this paper, different milling conditions are estimated as the input variables, tool wear loss is estimated as the output variable, and projection pursuit regression (PPR) method is proposed to establish the relationship between the input and the output variables. A real-time tool wear loss estimator is developed based on the PPR model, the experimental and estimated results are found to be in satisfactory agreement with average error lower than 10%.