Towards Design Automation for Additive Manufacturing : A Multidisciplinary Optimization approach

This paper studies how to control boundary slope of optimized parts in density-based topology optimization for additive manufacturing (AM). Boundary slope of a part affects the amount of support structure required during its fabrication by additive processes. Boundary slope also has a direct relation with the resulting surface roughness from the AM processes, which in turn affects the heat transfer efficiency. By constraining the minimal boundary slope, support structures can be eliminated or reduced for AM, and thus, material and postprocessing costs are reduced; by constraining the maximal boundary slope, high-surface roughness can be attained, and thus, the heat transfer efficiency is increased. In this paper, the boundary slope is controlled through a constraint between the density gradient and the given build direction. This allows us to explicitly control the boundary slope through density gradient in the density-based topology optimization approach. We control the boundary slope through two single global constraints. An adaptive scheme is also proposed to select the thresholds of these two boundary slope constraints. Numerical examples of linear elastic problem, heat conduction problem, and thermoelastic problems demonstrate the effectiveness and efficiency of the proposed formulation in controlling boundary slopes for additive manufacturing. Experimental results from metal 3D printed parts confirm that our boundary slope-based formulation is effective for controlling part self-support during printing and for affecting surface roughness of the printed parts.

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Optimize Additive Manufacturing Post-Build Heat Treatment and Hot Iso-Static Pressing Process Using an Integrated Computational Materials Engineering Framework

Volume 2: Advanced Manufacturing ◽

10.1115/imece2018-88550 ◽

2018 ◽

Cited By ~ 1

Author(s):

Anahita Imanian ◽

Kelvin Leung ◽

Nagaraja Iyyer ◽

Peipei Li ◽

Derek H. Warner

Keyword(s):

Heat Treatment ◽

Additive Manufacturing ◽

Process Parameters ◽

Fatigue Performance ◽

Optimization Approach ◽

Materials Engineering ◽

Integrated Computational Materials Engineering ◽

Computational Materials ◽

Static Pressing ◽

Hip Process

Additive manufacturing (AM) technology is becoming more popular for the fabrication of 3D metal products as it offers rapid prototyping and large design freedom. However, part quality and fatigue performance of components fabricated by current AM technology are not comparable to that produced by traditional methods. Post-build processing techniques, such as heat treatment (HT) and Hot Iso-static Pressing (HIP), have been developed to improve microstructure and remove internal flaws that are detrimental to fatigue resistance. In order to simulate the HT and HIP process and optimize the post-build process, an integrated computational materials engineering (ICME) approach is utilized to link the process parameters with material’s structures, properties, and fatigue performance. The purpose of this study is two-fold. First, we simulate the HT/HIP process including the physics of heat transfer, and porosity evolution. Second, a state-of-the-art hybrid optimization approach, combining response surface method and genetic algorithm is utilized to optimize the post-build process parameters in order to minimize porosities.

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