When AI meets additive manufacturing: Challenges and emerging opportunities for human-centered products development
Nowadays, additive manufacturing (AM) has been increasingly leveraged to produce human-
centered products, such as orthoses and prostheses as well as therapeutic helmets, finger …
centered products, such as orthoses and prostheses as well as therapeutic helmets, finger …
Leveraging small-scale datasets for additive manufacturing process modeling and part certification: Current practice and remaining gaps
Additive manufacturing (AM) provides a data-rich environment for collecting a variety of
process data. These crucial data can be used to develop effective machine learning (ML) …
process data. These crucial data can be used to develop effective machine learning (ML) …
Morphological dynamics-based anomaly detection towards in situ layer-wise certification for directed energy deposition processes
The process uncertainty induced quality issue remains the major challenge that hinders the
wider adoption of additive manufacturing (AM) technology. The defects occurred significantly …
wider adoption of additive manufacturing (AM) technology. The defects occurred significantly …
Design de-identification of thermal history for collaborative process-defect modeling of directed energy deposition processes
There is an urgent need for develo** collaborative process-defect modeling in metal-
based additive manufacturing (AM). This mainly stems from the high volume of training data …
based additive manufacturing (AM). This mainly stems from the high volume of training data …
Real-time monitoring and quality assurance for laser-based directed energy deposition: integrating co-axial imaging and self-supervised deep learning framework
Artificial Intelligence (AI) has emerged as a promising solution for real-time monitoring of the
quality of additively manufactured (AM) metallic parts. This study focuses on the Laser …
quality of additively manufactured (AM) metallic parts. This study focuses on the Laser …
Diffusion generative model-based learning for smart layer-wise monitoring of additive manufacturing
E Yangue, D Fullington, O Smith… - … of Computing and …, 2024 - asmedigitalcollection.asme.org
Despite the rapid adoption of deep learning models in additive manufacturing (AM),
significant quality assurance challenges continue to persist. This is further emphasized by …
significant quality assurance challenges continue to persist. This is further emphasized by …
Monitoring melted state of reinforced particle in metal matrix composite fabricated by laser melt injection using optical camera
H Xu, H Huang - The International Journal of Advanced Manufacturing …, 2023 - Springer
Laser melt injection (LMI) is a promising technique for the fabrication of particle reinforced
metal matrix composites (MMCs), in which process monitoring is highly demanded to ensure …
metal matrix composites (MMCs), in which process monitoring is highly demanded to ensure …
Ontology-guided attribute learning to accelerate certification for develo** new printing processes
Identifying printing defects is vital for process certification, especially with evolving printing
technologies. However, this task proves challenging, especially for micro-level defects …
technologies. However, this task proves challenging, especially for micro-level defects …
DP-SGD-global-adapt-V2-S: Triad improvements of privacy, accuracy and fairness via step decay noise multiplier and step decay upper clip** threshold
Abstract Differentially Private Stochastic Gradient Descent (DP-SGD) has become a widely
used technique for safeguarding sensitive information in deep learning applications …
used technique for safeguarding sensitive information in deep learning applications …
Evaluation of design information disclosure through thermal feature extraction in metal based additive manufacturing
Abstract Manufacturing-as-a-Service (MaaS) can accelerate additive manufacturing (AM)
process-defect modeling by augmenting training data to all collaborating users via a data …
process-defect modeling by augmenting training data to all collaborating users via a data …