A reverse engineering methodology for rotary components from point cloud data

This paper presents data analysis and model generation techniques for reverse engineering rotary components such as shafts and rotary dies. Existing reverse engineering techniques create a computer-aided design model from point cloud data that are a mathematical ‘best fit’, but this may be an inaccurate representation due to noise contained in the model. Also, rotary components have their own set of design parameters and reverse engineering design challenges. For several rotary applications, the point cloud data go through a series of transformations (such as transforming the points from a rotational to a planar representation) in order to extract the relevant information, and then a ‘healing’ process is performed to modify critical geometry and dimensions. To meet these challenges, a systematic approach is adopted in a comprehensive manner to extract the relevant information and transform it into relevant design knowledge. Several practical examples are presented that highlight the issues, the reverse engineering methodology, and how these techniques provide a platform for any subsequent design modifications and the component manufacture.