Prediction of toolpath redundancy for NC machining of free-form surfaces based on automatic recognition of steep-wall features

Abstract

The degree of toolpath redundancy is a critical concern when looking for an appropriate toolpath strategy for free-form surface machining. Hence, quantitative analysis of toolpath redundancy is important to CAM applications. In this work, a novel approach for prediction of toolpath redundancy for free-form surface machining is proposed. Firstly, a general mathematical model to represent toolpath redundancy rate is proposed based on the analysis of local toolpath intervals and their difference from the optimal values. And then, taking the most widely used iso-planar machining as case study, the steep-wall features that bring in the variation of surface slope rates alone machining strips are identified as the main cause of the generation of toolpath redundancy, so a method to automatic recognising steep-wall features from free-form surface is developed. At last, based on the steep-wall feature segmentation, an algorithm is presented to quantitatively predict the toolpath redundancy rate for free-form surface machining. A comparison study is made between the predicted redundancy rates and the experimental results by a number of case studies. The results have validated that the proposed approach can effectively predict the redundancy rate for a surface machining case before the real toolpaths to be generated.