Computational 3D - 4D - 5D Manufacturing

Hybrid Manufacturing (HM) combining Additive Manufacturing (AM) and subtractive machining (SM) technologies have recently been introduced and have the potential to address the shortcomings of AM. Once such example of an HM machine is the DMG Mori Lasertec 65. These 5 axis machines allow for rapid deposition of material during additive manufacturing, and address the issues of feature resolution, surface finish and tolerances by subtractive machining.  Additionally, these processes allow for the creation of complex geometries not possible with standard 5 axis machining.  Process planning for HM is fairly complex manual task and could benefit from automation.  Key steps in process planning are the decomposition of the part into additive and subtractive features, sequencing the features and planning the tool path for these features.  This project presents algorithms for decomposing the part and sequencing the additive and subtractive features in an automated manner, paving the way for a fully automated systems for HM. Examples of a wide range of parts demonstrating the capability of the algorithm are presented.

Traditionally Additive Manufacturing (AM) is often limited to 3-axis deposition of the layers, with the sliced geometry for each layer based on a vertical build direction.  The restriction forces the requirement for support structures for overhanging areas of the part, often necessitating the need for additional work to remove the support structures.  Allowing for multi-axis machines has the potential to reorient the parts and create AM parts by eliminating the support structures.  Successful automated implementation of this strategy requires that the part be decomposed into volumes such that the individual volumes can still be processed by slicing in the X-Y plane and building in the z-direction, while allowing for reorientation of the part for each decomposed volume. This is one of the first steps in process planning, and also in assessing the feasibility of making the part on a 3+2 axis machine.  In this project, we present a decomposition algorithm that determines orientation and the decomposition sequence and for the decomposed volumes using a 3+2 axis machine. 

The role of Shape Retrieval Tools (SRTs) has assumed importance as they can help designers search and retrieve similar part models from various sources (databases, web, etc) based on a rough-cut model of a desired or target 3D model. Current evaluation methods, such as precision and recall are based on human interpretation of the retrieval results. An algorithm is proposed to objectively analyze the search results based on Model Match Ratio (MMR) which is computed based on the variance between the input and retrieved geometry of the 3D models in reference. A Precision Sequence Metric (PSM) is developed by ranking the retrieved results based on the MMR for evaluating quality of the search. The proposed MMR algorithm and PSM have been implemented in Python and CloudCompare.