Topology optimization including a model of the layer-by-layer additive manufacturing process

TL;DR

This paper presents a topology optimization method that incorporates layer-by-layer additive manufacturing models, addressing issues like overhang and residual stresses, and demonstrating fast convergence and practical applicability.

Contribution

It introduces a multi-objective topology optimization framework that models the AM process, including overhang and residual stresses, with proven convergence and open-source implementation.

Findings

Convergence of the model is theoretically proven and numerically fast.

The approach effectively avoids drips and sharp corners in designs.

Open-source Python codes are provided for reproducibility.

Abstract

A topology optimization formulation including a model of the layer-by-layer additive manufacturing (AM) process is considered. Defined as a multi-objective minimization problem, the formulation accounts for the performance and cost of both the final and partially manufactured designs and allows for considering AM-related issues such as overhang and residual stresses in the optimization. The formulation is exemplified by stiffness optimization in which the overhang is limited by adding mechanical or thermal compliance as a measure of the cost of partially manufactured designs. Convergence of the model as the approximate layer-by-layer model is refined is shown theoretically, and an extensive numerical study indicates that this convergence can be fast, thus making it a computationally viable approach useful for including AM-related issues into topology optimization. The examples also show that drips and sharp corners associated with some geometry-based formulations for overhang limitation can be avoided. The codes used in this article are written in Python using only open sources libraries and are available for reference.