Curve-guided 5-axis CNC flank milling of free-form surfaces using custom-shaped tools

A new method for 5-axis flank milling of free-form surfaces is proposed. Existing flank milling path-planning methods typically use on-market milling tools whose shape is cylindrical or conical, and is therefore not well-suited for meeting fine tolerances for manufacturing of benchmark free-form surfaces like turbine blades, gears, or blisks. In contrast, our optimization-based framework incorporates the shape of the tool into the optimization cycle and looks not only for the milling paths, but also for the shape of the tool itself. Given a free-form reference surface and a guiding path that roughly indicates the motion of the milling tool, tangential movability of quadruplets of spheres centered along a straight line is analyzed to indicate possible shapes and their motions. This results in $G^1$ Hermite data in the space of rigid body motions that are interpolated and further optimized, both in terms of the motion and the shape of the milling tool itself. We demonstrate our algorithm on synthetic free-form surfaces and industrial benchmark datasets, showing that the use of custom-shaped tools is capable of meeting fine industrial tolerances and outperforms the use of classical, on-market tools.RYC-2017-2264

From computer-aided to intelligent machining: Recent advances in computer numerical control machining research

The aim of this paper is to provide an introduction and overview of recent advances in the key technologies and the supporting computerized systems, and to indicate the trend of research and development in the area of computational numerical control machining. Three main themes of recent research in CNC machining are simulation, optimization and automation, which form the key aspects of intelligent manufacturing in the digital and knowledge based manufacturing era. As the information and knowledge carrier, feature is the efficacious way to achieve intelligent manufacturing. From the regular shaped feature to freeform surface feature, the feature technology has been used in manufacturing of complex parts, such as aircraft structural parts. The authors’ latest research in intelligent machining is presented through a new concept of multi-perspective dynamic feature (MpDF), for future discussion and communication with readers of this special issue. The MpDF concept has been implemented and tested in real examples from the aerospace industry, and has the potential to make promising impact on the future research in the new paradigm of intelligent machining. The authors of this paper are the guest editors of this special issue on computational numerical control machining. The guest editors have extensive and complementary experiences in both academia and industry, gained in China, USA and UK

Characterizing envelopes of moving rotational cones and applications in CNC machining

Motivated by applications in CNC machining, we provide a characterization of surfaces which are enveloped by a one-parametric family of congruent rotational cones. As limit cases, we also address ruled surfaces and their offsets. The characterizations are higher order nonlinear PDEs generalizing the ones by Gauss and Monge for developable surfaces and ruled surfaces, respectively. The derivation includes results on local approximations of a surface by cones of revolution, which are expressed by contact order in the space of planes. To this purpose, the isotropic model of Laguerre geometry is used as there rotational cones correspond to curves (isotropic circles) and higher order contact is computed with respect to the image of the input surface in the isotropic model. Therefore, one studies curve-surface contact that is conceptually simpler than the surface-surface case. We show that, in a generic case, there exist at most six positions of a fixed rotational cone that have third order contact with the input surface. These results are themselves of interest in geometric computing, for example in cutter selection and positioning for flank CNC machining.RYC-2017-2264