[HTML][HTML] Big data, machine learning, and digital twin assisted additive manufacturing: A review

L **, X Zhai, K Wang, K Zhang, D Wu, A Nazir, J Jiang… - Materials & Design, 2024 - Elsevier
Additive manufacturing (AM) has undergone significant development over the past decades,
resulting in vast amounts of data that carry valuable information. Numerous research studies …

[HTML][HTML] Enhancing property prediction and process optimization in building materials through machine learning: A review

K Stergiou, C Ntakolia, P Varytis, E Koumoulos… - Computational Materials …, 2023 - Elsevier
Abstract Analysis and design, as the most critical components in material science, require a
highly rigorous approach to assure long-term success. Due to a recent increase in the …

A systematic literature review on recent trends of machine learning applications in additive manufacturing

MD Xames, FK Torsha, F Sarwar - Journal of Intelligent Manufacturing, 2023 - Springer
Additive manufacturing (AM) offers the advantage of producing complex parts more
efficiently and in a lesser production cycle time as compared to conventional subtractive …

[HTML][HTML] Optimization of FFF process parameters by naked mole-rat algorithms with enhanced exploration and exploitation capabilities

JS Chohan, N Mittal, R Kumar, S Singh, S Sharma… - Polymers, 2021 - mdpi.com
Fused filament fabrication (FFF) has numerous process parameters that influence the
mechanical strength of parts. Hence, many optimization studies are performed using …

Machine learning model for predicting the hardness of additively manufactured acrylonitrile butadiene styrene

D Veeman, S Sudharsan, GJ Surendhar… - Materials Today …, 2023 - Elsevier
Additive manufacturing is an incipient technology with great potential to achieve excellent
mechanical properties with minimal material wastage. Additive manufacturing is well known …

[HTML][HTML] Build orientation optimization based on weighted analysis of local surface region curvature

H Guo, J Xu, S Zhang, G Yi - Applied Sciences, 2020 - mdpi.com
Build orientation becomes a hot issue in 3D printing, which has a significant impact on the
surface quality, support structure and final cost of the fabricated model. In this paper, we …

Investigations and predictions for mechanical and surface properties of FFF prints using DOE, ML and FEA

A Kumar, KS Boparai, JS Chohan… - Advances in Materials …, 2024 - Taylor & Francis
In the past two decades, number of studies have been reported on process parametric
optimisation of the fused filament fabrication (FFF) process for polylactic acid-based …

Optimized printing orientation determination for improving the stiffness of as-printed handles

W Pan, X Chen, W Liu, L Qiao, H Kuang… - Rapid Prototy** …, 2025 - emerald.com
Purpose This study aims to improve the stiffness of as-printed handles by finding appropriate
printing orientations. Design/methodology/approach First, a series of benchmark handles is …

Mechanical performance optimization in FFF 3D printing using Taguchi design and machine learning approach with PLA/walnut Shell composites filaments

F Kartal - Journal of Vinyl and Additive Technology, 2025 - Wiley Online Library
This study explores the optimization of mechanical properties in 3D‐printed components
made from a Polylactic Acid (PLA) and Walnut Shell Composite using Fused Filament …

[PDF][PDF] AI-Augmented Finite Difference Methods for Solving PDES: Advancing Numerical Solutions in Mathematical Modeling

J Okwuwe, OE Oduselu-Hassan - Asian Journal of Mathematics …, 2024 - researchgate.net
This study explores the integration of artificial intelligence (AI) with finite difference methods
(FDM) to enhance the numerical solution of partial differential equations (PDEs) in physics …