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 …

Machine learning for metal additive manufacturing: Towards a physics-informed data-driven paradigm

S Guo, M Agarwal, C Cooper, Q Tian, RX Gao… - Journal of Manufacturing …, 2022 - Elsevier
Abstract Machine learning (ML) has shown to be an effective alternative to physical models
for quality prediction and process optimization of metal additive manufacturing (AM) …

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 …

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 …

A physics-informed machine learning model for porosity analysis in laser powder bed fusion additive manufacturing

R Liu, S Liu, X Zhang - The International Journal of Advanced …, 2021 - Springer
To control part quality, it is critical to analyze pore generation mechanisms, laying theoretical
foundation for future porosity control. Current porosity analysis models use machine setting …

Process optimization of complex geometries using feed forward control for laser powder bed fusion additive manufacturing

CL Druzgalski, A Ashby, G Guss, WE King… - Additive …, 2020 - Elsevier
Additive manufacturing (AM) enables the fabrication of complex designs that are difficult to
create by other means. Metal parts manufactured by laser powder bed fusion (LPBF) can …

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 …

A stochastic scan strategy for grain structure control in complex geometries using electron beam powder bed fusion

A Plotkowski, J Ferguson, B Stump, W Halsey… - Additive …, 2021 - Elsevier
Spatial control of microstructure within a three-dimensional component has been a dream of
materials scientists for centuries. However, limitations in traditional manufacturing processes …

Microstructure and properties of additively manufactured Al–Ce–Mg alloys

K Sisco, A Plotkowski, Y Yang, D Leonard, B Stump… - Scientific Reports, 2021 - nature.com
Additive manufacturing of aluminum alloys is largely dominated by a near-eutectic Al-Si
compositions, which are highly weldable, but have mechanical properties that are not …

Photodiode-based machine learning for optimization of laser powder bed fusion parameters in complex geometries

S Lapointe, G Guss, Z Reese, M Strantza… - Additive …, 2022 - Elsevier
The quality of parts produced through laser powder bed fusion additive manufacturing can
be irregular, with complex geometries sometimes exhibiting dimensional inaccuracies and …