Review of transfer learning in modeling additive manufacturing processes
Modeling plays an important role in the additive manufacturing (AM) process and quality
control. In practice, however, only limited data are available for each product due to the …
control. In practice, however, only limited data are available for each product due to the …
When AI meets additive manufacturing: Challenges and emerging opportunities for human-centered products development
Nowadays, additive manufacturing (AM) has been increasingly leveraged to produce human-
centered products, such as orthoses and prostheses as well as therapeutic helmets, finger …
centered products, such as orthoses and prostheses as well as therapeutic helmets, finger …
[HTML][HTML] Predicting stress–strain curves using transfer learning: Knowledge transfer across polymer composites
The engineering stress–strain curve of a material allows one to determine mechanical
properties such as elastic modulus, strength, and toughness. While machine learning has …
properties such as elastic modulus, strength, and toughness. While machine learning has …
Direct aging of additively manufactured A20X aluminum alloy
H Karimialavijeh, M Ghasri-Khouzani… - Journal of Alloys and …, 2023 - Elsevier
This study investigates the effect of direct aging on a newly developed high-performance
aluminum alloy A20X for laser powder bed fusion. Three different temperatures (180° C …
aluminum alloy A20X for laser powder bed fusion. Three different temperatures (180° C …
Geometric accuracy prediction and improvement for additive manufacturing using triangular mesh shape data
One major impediment to wider adoption of additive manufacturing (AM) is the presence of
larger-than-expected shape deviations between an actual print and the intended design …
larger-than-expected shape deviations between an actual print and the intended design …
Learning and predicting shape deviations of smooth and non-smooth 3d geometries through mathematical decomposition of additive manufacturing
In additive manufacturing (AM), final product geometries are often deformed or distorted. The
deviations of three-dimensional (3D) shapes from their intended designs can be …
deviations of three-dimensional (3D) shapes from their intended designs can be …
Design de-identification of thermal history for collaborative process-defect modeling of directed energy deposition processes
There is an urgent need for developing collaborative process-defect modeling in metal-
based additive manufacturing (AM). This mainly stems from the high volume of training data …
based additive manufacturing (AM). This mainly stems from the high volume of training data …
In situ monitoring of optical emission spectra for microscopic pores in metal additive manufacturing
Quality assurance techniques are increasingly demanded in additive manufacturing. Going
beyond most of the existing research that focuses on the melt pool temperature monitoring …
beyond most of the existing research that focuses on the melt pool temperature monitoring …
Physics-Informed Approximation of Internal Thermal History for Surface Deformation Predictions in Wire Arc Directed Energy Deposition
This work presents a physics-informed fusion methodology for deformation detection using
multi-sensor thermal data. A challenge with additive manufacturing (AM) is that …
multi-sensor thermal data. A challenge with additive manufacturing (AM) is that …
Improved modeling of kinematics-induced geometric variations in extrusion-based additive manufacturing through between-printer transfer learning
For extrusion-based additive manufacturing, the variation in material deposition can
significantly affect printed material distribution, causing infill nonuniformity and defects …
significantly affect printed material distribution, causing infill nonuniformity and defects …