Towards the next generation of machine learning models in additive manufacturing: A review of process dependent material evolution

M Parsazadeh, S Sharma, N Dahotre - Progress in Materials Science, 2023 - Elsevier
Additive manufacturing facilitates producing of complex parts due to its design freedom in a
wide range of applications. Despite considerable advancements in additive manufacturing …

A review of machine learning techniques for process and performance optimization in laser beam powder bed fusion additive manufacturing

J Liu, J Ye, D Silva Izquierdo, A Vinel… - Journal of Intelligent …, 2023 - Springer
Laser beam powder bed fusion (LB-PBF) is a widely-used metal additive manufacturing
process due to its high potential for fabrication flexibility and quality. Its process and …

When AI meets additive manufacturing: Challenges and emerging opportunities for human-centered products development

C Liu, W Tian, C Kan - Journal of Manufacturing Systems, 2022 - Elsevier
Nowadays, additive manufacturing (AM) has been increasingly leveraged to produce human-
centered products, such as orthoses and prostheses as well as therapeutic helmets, finger …

Applications of machine learning in process monitoring and controls of L-PBF additive manufacturing: A review

D Mahmoud, M Magolon, J Boer, MA Elbestawi… - Applied Sciences, 2021 - mdpi.com
One of the main issues hindering the adoption of parts produced using laser powder bed
fusion (L-PBF) in safety-critical applications is the inconsistencies in quality levels …

State-of-the-art review of machine learning applications in additive manufacturing; from design to manufacturing and property control

GK Sarkon, B Safaei, MS Kenevisi, S Arman… - … Methods in Engineering, 2022 - Springer
In this review, some of the latest applicable methods of machine learning (ML) in additive
manufacturing (AM) have been presented and the classification of the most common ML …

Digitally twinned additive manufacturing: Detecting flaws in laser powder bed fusion by combining thermal simulations with in-situ meltpool sensor data

R Yavari, A Riensche, E Tekerek, L Jacquemetton… - Materials & Design, 2021 - Elsevier
The goal of this research is the in-situ detection of flaw formation in metal parts made using
the laser powder bed fusion (LPBF) additive manufacturing process. This is an important …

A systematic review on data of additive manufacturing for machine learning applications: the data quality, type, preprocessing, and management

Y Zhang, M Safdar, J Xie, J Li, M Sage… - Journal of Intelligent …, 2023 - Springer
Additive manufacturing (AM) techniques are maturing and penetrating every aspect of the
industry. With more and more design, process, structure, and property data collected …

Recent developments in the application of machine-learning towards accelerated predictive multiscale design and additive manufacturing

SS Babu, AHI Mourad, KH Harib… - Virtual and Physical …, 2023 - Taylor & Francis
The application of three-dimensional (3D) printing/Additive Manufacturing (AM) for
developing multi-functional smart/intelligent composite materials is a highly promising area …

Detection, classification and prediction of internal defects from surface morphology data of metal parts fabricated by powder bed fusion type additive manufacturing …

Y Gui, K Aoyagi, H Bian, A Chiba - Additive Manufacturing, 2022 - Elsevier
In powder bed fusion type additive manufacturing using an electron beam (PBF-EB), various
process parameters have a significant influence on the performance of manufactured parts …

Cu10Sn to Ti6Al4V bonding mechanisms in laser-based powder bed fusion multiple material additive manufacturing with different build strategies

C Wei, L Liu, H Cao, X Zhong, X Xu, Y Gu, D Cheng… - Additive …, 2022 - Elsevier
Additive manufacturing of titanium alloy (TiA)–copper alloy (CuA) multiple material
components poses many challenges due to the significant differences in their material …