Using Topology Optimization to Reduce Support Structures in Additive Manufacturing

University Of Wisconsin-Madison, Madison WI

Investigators

Abstract

Additive manufacturing represents a class of processes for fabricating parts of virtually any shape through material addition. The technique, often called 3D printing, offers several advantages over traditional manufacturing, and has the potential to revolutionize the way things are made. However, to fully exploit additive manufacturing, new design methods are needed. This award supports fundamental research towards developing a design framework for additive manufacturing. The design framework will not only consider traditional performance metrics but also additive manufacturing constraints. Specifically, the award will focus on the reduction of the sacrificial support structures needed to additively manufacture parts with geometric overhangs. By departing from conventional practice for support-structure design, the project's integrated approach will lead to low-cost products, benefitting the U.S. economy and society. Developing the framework involves several disciplines including design, manufacturing, and computer science. The research will help broaden participation of underrepresented groups and positively impact engineering education. This research will leverage topology optimization theory to integrate performance metrics and additive manufacturing constraints. For example, it will help minimize the compliance of the part, while respecting support structure constraints. The framework will be sufficiently general to accommodate a variety of performance metrics such as compliance, stress, and buckling, and a variety of additive manufacturing constraints such as support structures, surface roughness, and fabrication time. Robust level-set methods of topology optimization will be combined with augmented Lagrangian formulations to create a design framework that will then be integrated into these existing computer aided design systems and made available to the public. Experimental calibration and validation will be carried out to support the theory. The focus will largely be on polymer fused deposition modeling since this process is both inexpensive and easily accessible. However, experiments will also be carried out on metal additive manufacturing to establish the broader implications of the findings.