3D printing and implementation of digital twins: Current trends and limitations

A Kantaros, D Piromalis, G Tsaramirsis… - Applied System …, 2021 - mdpi.com
Fabricating objects with desired mechanical properties by utilizing 3D printing methods can
be expensive and time-consuming, especially when based only on a trial-and-error test …

Artificial intelligence‐augmented additive manufacturing: insights on closed‐loop 3D printing

AR Sani, A Zolfagharian… - Advanced Intelligent …, 2024 - Wiley Online Library
The advent of 3D printing has transformed manufacturing. However, extending the library of
materials to improve 3D printing quality remains a challenge. Defects can occur when …

A few shot classification methods based on multiscale relational networks

W Zheng, X Tian, B Yang, S Liu, Y Ding, J Tian, L Yin - Applied Sciences, 2022 - mdpi.com
Learning information from a single or a few samples is called few-shot learning. This
learning method will solve deep learning's dependence on a large sample. Deep learning …

Toward accurate fused deposition modeling 3d printer fault detection using improved YOLOv8 with hyperparameter optimization

NBA Karna, MAP Putra, SM Rachmawati… - IEEE …, 2023 - ieeexplore.ieee.org
This research article presents an enhanced YOLOv8 model with an additional feature
extraction layer integrated into the traditional YOLOv8 architecture to improve fault detection …

A low-cost multi-sensor data acquisition system for fault detection in fused deposition modelling

S Kumar, T Kolekar, S Patil, A Bongale, K Kotecha… - Sensors, 2022 - mdpi.com
Fused deposition modelling (FDM)-based 3D printing is a trending technology in the era of
Industry 4.0 that manufactures products in layer-by-layer form. It shows remarkable benefits …

[HTML][HTML] A review of AI for optimization of 3D printing of sustainable polymers and composites

M Hassan, M Misra, GW Taylor, AK Mohanty - Composites Part C: Open …, 2024 - Elsevier
In recent years, 3D printing has experienced significant growth in the manufacturing sector
due to its ability to produce intricate and customized components. The advent of Industry 4.0 …

Predicting defects in laser powder bed fusion using in-situ thermal imaging data and machine learning

SM Estalaki, CS Lough, RG Landers, EC Kinzel… - Additive …, 2022 - Elsevier
Variation in the local thermal history during the Laser Powder Bed Fusion (LPBF) process in
Additive Manufacturing (AM) can cause micropore defects, which add to the uncertainty of …

[HTML][HTML] Optimization of 4D/3D printing via machine learning: A systematic review

YA Alli, H Anuar, MR Manshor, CE Okafor… - Hybrid Advances, 2024 - Elsevier
This systematic review explores the integration of 4D/3D printing technologies with machine
learning, sha** a new era of manufacturing innovation. The analysis covers a wide range …

In situ process monitoring using acoustic emission and laser scanning techniques based on machine learning models

K Xu, J Lyu, S Manoochehri - Journal of Manufacturing Processes, 2022 - Elsevier
Abstract Fused Filament Fabrication (FFF) is a widely used additive manufacturing method
for obtaining prototypes with complex structures. On the other hand, Commercial FFF …

[HTML][HTML] Exploring the integration of digital twin and additive manufacturing technologies

N Jyeniskhan, K Shomenov, MH Ali… - International Journal of …, 2024 - Elsevier
This paper offers a comprehensive overview of recent advancements in digital twin
technology applied to additive manufacturing (AM), focusing on recent research trends …