Converting Multi-Axis Machine Tools into Subtractive 3D Printers by using Intelligent Discrete Geometry Data Structures

Abstract:

The overarching goal of this project is to develop a novel cyberphysical platform for fast and efficient, fully digital, 3-dimensional, 5-axis machining. Proposed methodology is inspired by 3D printing, which is easy to program but limited in terms of the materials that can be used, the finishing quality that can be achieved, and relatively slow printing speeds. By contrast, CNC milling can address these limitations. However, the current approaches in commercial CAD/CAM packages lack the capability of automated generation of collision free tool paths for multi-axis CNC machines. Such a steep productivity limitation in conventional subtractive machining process leads to significantly higher manufacturing cost for CNC-based prototyping, as it mandates advanced human expertise for sophisticated CAD/CAM modeling and tremendous time investment due to manual tuning of the design parameters. Proposed cyberphysical platform would bring classical subtractive manufacturing back into the arsenal of rapid prototyping, providing users of typical CNC (computer numerical control) machine tools with the ability to quickly determine if a part can be produced on a specific machine and machine the part. The platform will help to reduce the cost and improve the quality of manufactured parts. Furthermore, it would allow rapid deployment of new innovations in components that require machining. The technical approach brings modern computer science to bear on problems of manufacturing. In particular, the project's investigations focus on how to exploit emerging massively parallel computing platforms such as general purpose graphics coprocessors (GPUs), many-core processors, and cloud computing to solve machining design and analysis problems much faster than they are today.