[HTML][HTML] Big data, machine learning, and digital twin assisted additive manufacturing: A review
Additive manufacturing (AM) has undergone significant development over the past decades,
resulting in vast amounts of data that carry valuable information. Numerous research studies …
resulting in vast amounts of data that carry valuable information. Numerous research studies …
A systematic review on data of additive manufacturing for machine learning applications: the data quality, type, preprocessing, and management
Additive manufacturing (AM) techniques are maturing and penetrating every aspect of the
industry. With more and more design, process, structure, and property data collected …
industry. With more and more design, process, structure, and property data collected …
[HTML][HTML] A review of machine learning (ML) and explainable artificial intelligence (XAI) methods in additive manufacturing (3D printing)
Additive Manufacturing (AM)(known as 3D printing) has modernised traditional
manufacturing processes by enabling the layer-by-layer fabrication of complex geometries …
manufacturing processes by enabling the layer-by-layer fabrication of complex geometries …
Guiding the optimization of membraneless microfluidic fuel cells via explainable artificial intelligence: Comparative analyses of multiple machine learning models and …
Membraneless microfluidic fuel cells (MMFCs) offer great potential for clean energy
production, but their expense and tedious optimization process have limited their wider use …
production, but their expense and tedious optimization process have limited their wider use …
Physics-informed machine learning for accurate prediction of temperature and melt pool dimension in metal additive manufacturing
The temperature distribution and melt pool size have a great influence on the microstructure
and mechanical behavior of metal additive manufacturing process. The numerical method …
and mechanical behavior of metal additive manufacturing process. The numerical method …
Smart optimization and investigation of a PCMs-filled helical finned-tubes double-pass solar air heater: An experimental data-driven deep learning approach
Abstract Solar Air Heaters (SAHs), widely utilized for space heating and drying in residential
and commercial settings, exhibit performance dependent on several operational …
and commercial settings, exhibit performance dependent on several operational …
Data-driven prediction of keyhole features in metal additive manufacturing based on physics-based simulation
The defect formation is closely related to molten pool and keyhole features in metal additive
manufacturing. Experimentation and physics-based simulation methods to capture the …
manufacturing. Experimentation and physics-based simulation methods to capture the …
Real-time prediction and adaptive adjustment of continuous casting based on deep learning
Digitalisation of metallurgical manufacturing, especially technological continuous casting
using numerical models of heat and mass transfer and subsequent solidification has been …
using numerical models of heat and mass transfer and subsequent solidification has been …
Advancing additive manufacturing through deep learning: A comprehensive review of current progress and future challenges
This paper presents the first comprehensive literature review of deep learning (DL)
applications in additive manufacturing (AM). It addresses the need for a thorough analysis in …
applications in additive manufacturing (AM). It addresses the need for a thorough analysis in …
Optimizing laser power of directed energy deposition process for homogeneous AISI M4 steel microstructure
RT Jardin, V Tuninetti, JT Tchuindjang… - Optics & Laser …, 2023 - Elsevier
A finite element model of directed energy deposition (DED) process predicts the thermal
history during the manufacturing of high speed steel cuboid samples. The simulation result …
history during the manufacturing of high speed steel cuboid samples. The simulation result …