Optimal Design for Metal Additive Manufacturing: An Integrated Computational Materials Engineering (ICME) Approach
JOM, vol. 72, pp. 1092–1104
Abstract
Abstract We present our latest results on linking the process–structure–properties–performance (PSPP) chain for metal additive manufacturing (AM), using a multi-scale and multi-physics integrated computational materials engineering (ICME) approach. The abundance of design parameters and the complex relationship between those and the performance of AM parts have so far impeded the widespread adoption of metal AM technologies for structurally critical load-bearing components. To unfold the full potential of metal AM, establishing a full quantitative PSPP linkage is essential. It will not only help in understanding the underlying physics but will also serve as a powerful and effective tool for optimal computational design. In this work, we illustrate an example of ICME-based PSPP linkage in metal AM, along with a hybrid physics-based data-driven strategy for its application in the optimal design of a component. Finally, we discuss our outlook for the improvement of each part in the computational linking of the PSPP chain.
Authors 7
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Affiliation as printed
ICME Group, Steel Institute, RWTH Aachen University, Aachen, Germany
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Affiliation as printed
ICME Group, Steel Institute, RWTH Aachen University, Aachen, Germany
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Affiliation as printed
ICME Group, Steel Institute, RWTH Aachen University, Aachen, Germany
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Affiliation as printed
ICME Group, Steel Institute, RWTH Aachen University, Aachen, Germany
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Affiliation as printed
ICME Group, Steel Institute, RWTH Aachen University, Aachen, Germany
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Affiliation as printed
Centre for Additive Manufacturing, School of Engineering, RMIT University, Melbourne, Australia
Centre for Additive Manufacturing, School of Engineering, RMIT University, Melbourne, VIC, Australia
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Affiliation as printed
ICME Group, Steel Institute, RWTH Aachen University, Aachen, Germany
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