Interference detection for direct tool path generation from measured data points

Abstract

One of the main issues of the reverse engineering (RE) is the duplication of an existing physical part whose geometric information is partially or completely unavailable in measured form. In some industrial applications, physical parts are duplicated using three-axis CNC machines and ball-end mills. Many researches studied the problem of direct tool path generation from measured data point. However, up to the present, it appears that there is no reported study on interference detection in paths generated directly from measured data points. Interference detection is a curial problem in direct tool path generation from measured data points. This paper discusses the problem of local and global interference detection for three-axis machining in RE and proposes algorithms for local and global interference detection. With these algorithms, the measured data points captured from a physical part are analyzed and classified according to the shapes of the part. The method has been tested with several industrial parts, and it is shown to be robust and efficient especially for the part with free-form surfaces.