Self-supporting structure design in additive manufacturing through explicit topology optimization

TL;DR

This paper introduces explicit topology optimization methods for designing self-supporting structures in additive manufacturing, eliminating the need for additional supports by optimizing explicit geometric parameters.

Contribution

It proposes two novel solution approaches based on MMC and MMV frameworks for AM-oriented topology optimization, addressing key theoretical and practical challenges.

Findings

Effective self-supporting structure designs demonstrated

Two optimization frameworks validated through numerical examples

Theoretical analysis of AM-specific topology optimization issues

Abstract

One of the challenging issues in additive manufacturing (AM) oriented topology optimization is how to design structures that are self-supportive in a manufacture process without introducing additional supporting materials. In the present contribution, it is intended to resolve this problem under an explicit topology optimization framework where optimal structural topology can be found by optimizing a set of explicit geometry parameters. Two solution approaches established based on the Moving Morphable Components (MMC) and Moving Morphable Voids (MMV) frameworks, respectively, are proposed and some theoretical issues associated with AM oriented topology optimization are also analyzed. Numerical examples provided demonstrate the effectiveness of the proposed methods.