A laminae approach to constructing geometric feature volumes

Abstract

The limiting factor for the majority of reported feature recognition (AFR) algorithms lie in their inability to handle anything more complex than the restricted geometric domain of 2.5D machined components. This paper describes a novel approach to recognising shape features on models comprising both simple and complex ruled surfaces. Specifically, the paper describes how the concept of 3D-laminae enables feature volumes bounded by complex ruled surfaces to be constructed. This generic feature recognition algorithm requires no predefined feature libraries and advocates the notion of neutral features, which separates the generic features identified by the extraction algorithm from those (features) classified subsequently to suit a discrete domain. The work concentrates on identifying machinable volumes (for manufacture by CNC machines) and the classifications presented apply specifically to this context. However, because the algorithm is capable of handling complex ruled surfaces, it is envisaged that the proposed methodology will be applicable to industries involved with the manufacture of dies and moulds.