A review of in-situ monitoring and process control system in metal-based laser additive manufacturing

Y Cai, J Xiong, H Chen, G Zhang - Journal of Manufacturing Systems, 2023 - Elsevier
Metal-based laser additive manufacturing (MLAM) is receiving significant attention in
industrial fields due to its capacity to manufacture complex and high-performance metal …

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 …

In-situ measurement and monitoring methods for metal powder bed fusion: an updated review

M Grasso, A Remani, A Dickins… - Measurement …, 2021 - iopscience.iop.org
The possibility of using a variety of sensor signals acquired during metal powder bed fusion
processes, to support part and process qualification and for the early detection of anomalies …

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 …

Real-time anomaly detection using convolutional neural network in wire arc additive manufacturing: molybdenum material

HW Cho, SJ Shin, GJ Seo, DB Kim, DH Lee - Journal of Materials …, 2022 - Elsevier
Wire arc additive manufacturing (WAAM) has received attention because of its high
deposition rate, low cost, and high material utilization. However, quality issues are critical in …

[HTML][HTML] Convolutional Neural Network applications in additive manufacturing: A review

M Valizadeh, SJ Wolff - Advances in Industrial and Manufacturing …, 2022 - Elsevier
Additive manufacturing (AM) is a promising digital manufacturing approach that has seen
recent rapid growth. Despite the fast-growing nature of the technology, AM has been slowed …

On the application of in-situ monitoring systems and machine learning algorithms for developing quality assurance platforms in laser powder bed fusion: A review

K Taherkhani, O Ero, F Liravi, S Toorandaz… - Journal of Manufacturing …, 2023 - Elsevier
Laser powder bed fusion (LPBF) is one class of metal additive manufacturing (AM) used to
fabricate high-quality complex-shape components. This technology has significantly …

A framework driven by physics-guided machine learning for process-structure-property causal analytics in additive manufacturing

H Ko, Y Lu, Z Yang, NY Ndiaye, P Witherell - Journal of Manufacturing …, 2023 - Elsevier
Abstract Data analytics with Machine Learning (ML) using physics knowledge and big data
offers high potential to continuously transform raw data to newfound knowledge of Process …

Deep learning-based data registration of melt-pool-monitoring images for laser powder bed fusion additive manufacturing

J Kim, Z Yang, H Ko, H Cho, Y Lu - Journal of Manufacturing Systems, 2023 - Elsevier
Melt-pool monitoring (MPM) has been widely used in the laser powder bed fusion (LPBF)
additive manufacturing process for process control and part quality prediction. Achieving this …

Thermal control of laser powder bed fusion using deep reinforcement learning

F Ogoke, AB Farimani - Additive Manufacturing, 2021 - Elsevier
Powder-based additive manufacturing techniques provide tools to construct intricate
structures that are difficult to manufacture using conventional methods. In Laser Powder Bed …