[HTML][HTML] Towards developing multiscale-multiphysics models and their surrogates for digital twins of metal additive manufacturing
Artificial intelligence (AI) embedded within digital models of manufacturing processes can be
used to improve process productivity and product quality significantly. The application of …
used to improve process productivity and product quality significantly. The application of …
The case for digital twins in metal additive manufacturing
DR Gunasegaram, AB Murphy… - Journal of Physics …, 2021 - iopscience.iop.org
The digital twin (DT) is a relatively new concept that is finding increased acceptance in
industry. A DT is generally considered as comprising a physical entity, its virtual replica, and …
industry. A DT is generally considered as comprising a physical entity, its virtual replica, and …
Modeling process–structure–property relationships in metal additive manufacturing: a review on physics-driven versus data-driven approaches
Metal additive manufacturing (AM) presents advantages such as increased complexity for a
lower part cost and part consolidation compared to traditional manufacturing. The multiscale …
lower part cost and part consolidation compared to traditional manufacturing. The multiscale …
Data-driven multi-scale multi-physics models to derive process–structure–property relationships for additive manufacturing
Additive manufacturing (AM) possesses appealing potential for manipulating material
compositions, structures and properties in end-use products with arbitrary shapes without …
compositions, structures and properties in end-use products with arbitrary shapes without …
Machine learning for metal additive manufacturing: Towards a physics-informed data-driven paradigm
Abstract Machine learning (ML) has shown to be an effective alternative to physical models
for quality prediction and process optimization of metal additive manufacturing (AM) …
for quality prediction and process optimization of metal additive manufacturing (AM) …
A digital twin hierarchy for metal additive manufacturing
Digital twins present a conceptual framework for product life-cycle monitoring and control
using a simulated replica of the physical system. Since their emergence, they have garnered …
using a simulated replica of the physical system. Since their emergence, they have garnered …
On the multiphysics modeling challenges for metal additive manufacturing processes
JG Michopoulos, AP Iliopoulos, JC Steuben… - Additive …, 2018 - Elsevier
In order to establish modeling and simulation (M&S) in support of Additive Manufacturing
Processes (AMP) control for tailoring functional component performance by design, a …
Processes (AMP) control for tailoring functional component performance by design, a …
A scalable digital platform for the use of digital twins in additive manufacturing
Abstract While Additive Manufacturing promises to reshape the manufacturing landscape,
challenges related to part, and process qualification hinder its widespread adoption. The …
challenges related to part, and process qualification hinder its widespread adoption. The …
Uncertainty quantification in metallic additive manufacturing through physics-informed data-driven modeling
The complicated metal-based additive manufacturing (AM) process involves various sources
of uncertainty, leading to variability in AM products. For comprehensive uncertainty …
of uncertainty, leading to variability in AM products. For comprehensive uncertainty …
Multiphysics multi-scale computational framework for linking process–structure–property relationships in metal additive manufacturing: a critical review
This review article provides a critical assessment of the progress made in computational
modelling of metal-based additive manufacturing (AM) with emphasis on its ability to predict …
modelling of metal-based additive manufacturing (AM) with emphasis on its ability to predict …