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

Abstract:

This grant provides funding for the formulation of a data model, and trajectory planning platform and methodology to execute a fully digital 3D, 5-axis machining capability. Research will be performed on methods for utilizing multiple Graphical Processor Units (GPUs), which are readily available, parallel digital processing hardware in these calculations. The methodology will be implemented in the context of an existing advanced computational framework that has tools for voxelization, variable resolution digital modeling, and parallel computing, integrating the fields of manufacturing and computer science. Experiments involving 5-axis machining will be executed to validate the methodology developed. Components will be machined and inspected on a coordinate measurement machine to verify that the target geometry has been achieved. If successful, this work will bring classical subtractive manufacturing back into  the arsenal of rapid prototyping, providing users of typical CNC machine tools with the ability to rapidly determine if a part can be produced on a specific machine and machine the part. Having such a design and analysis tool will help to reduce the cost, improve the quality and allow rapid deployment of new innovations in components that require machining. The proposed work will contribute to variable resolution digital representations to be employed in next generation digital manufacturing systems. It will also combine state-of-the-art concepts in computing and manufacturing to realize a completely new a cyber-physical approach to manufacturing.