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research-article

Concurrent Structure and Process Optimization for Minimum Cost Metal Additive Manufacturing

[+] Author and Article Information
Erva Ulu

Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
eulu@andrew.cmu.edu

Runze Huang

Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
hrzorel@gmail.com

Levent Burak Kara

Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
lkara@cmu.edu

Kate S. Whitefoot

Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213; Department of Engineering & Public Policy, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
kwhitefoot@cmu.edu

1Corresponding author.

ASME doi:10.1115/1.4042112 History: Received April 07, 2018; Revised November 17, 2018

Abstract

Metals-additive manufacturing (MAM) is enabling the possibility of significant environmental and economic benefits in many different industries. However, total production costs of MAM will need to be reduced substantially before it will be widely adopted across the manufacturing sector. Current topology optimization approaches focus on reducing material volume as a means of reducing material costs, but they do not account for other production costs that are influenced by a part's structure such as machine time and scrap. Moreover, concurrently optimizing MAM process variables with a part's structure has the potential to further reduce production costs. This paper demonstrates an approach to use process-based cost modeling in MAM topology optimization to minimize total production costs, including material, labor, energy, and machine costs, using cost estimates from industrial MAM operations. The approach is demonstrated on various 3D geometries for the electron beam melting process with Ti64 material. Concurrent optimization of the structures and process variables are compared to optimization of the structure alone. Results indicate that, once process variables are considered, more cost effective results can be obtained with similar amount of material through a combination of (1) building high stress regions with lower power to obtain larger yield strength and (2) increasing the power elsewhere to reduce the number of passes required, thereby reducing build time. In our case studies, concurrent optimization of part structure and MAM process parameters leads to up to 15% lower production costs and 21% faster build time than optimizing structure alone.

Copyright (c) 2018 by ASME
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