Digital Design Automation to Support In Situ Embedding of Functional Objects in Additive Manufacturing

Abstract

Additive manufacturing (AM) offers designers access to the entire volume of an artifact during its build operation, including the embedding of foreign objects, like sensors, motors, and actuators, into the artifact to produce multifunctional products from the build tray. However, the application of embedding requires extensive designer expertise in AM. This research aims to develop a tool to automate design decisions for in situ embedding, eliminating the need for ad hoc design decisions made by experts. Two unique approaches are proposed in this work: shadow projection and voxel simulation. Both of these approaches follow a three-stage methodology to achieve design automation by (1) identifying the optimum orientation for the object, (2) designing cavity, and finally (3) designing the shape converter for a flush surface at the paused layer. The two approaches differ in Stages 2 and 3. Where the shadow projection approach employs a series of point cloud manipulation to geometry of the embedded object, the voxel simulation approach simulates the process of insertion of the embedding geometry into the part voxel by voxel. While both proposed approaches are successful in automating design for embedding complex geometries, they result in tradeoffs between final designs and the time for computation. Computational experiment with six test cases shows that designers must strategically choose from one of the approaches to efficiently automate the digital design for embedding.