Towards real-time in-situ monitoring of hot-spot defects in L-PBF: A new classification-based method for fast video-imaging data analysis
M Bugatti, BM Colosimo - Journal of Intelligent Manufacturing, 2022 - Springer
The increasing interest towards additive manufacturing (AM) is pushing the industry to
provide new solutions to improve process stability. Monitoring is a key tool for this purpose …
provide new solutions to improve process stability. Monitoring is a key tool for this purpose …
In-situ monitoring in L-PBF: opportunities and challenges
BM Colosimo, M Grasso - Procedia CIRP, 2020 - Elsevier
In the recent years, several studies and industrial developments have been devoted to the
improvement of process repeatability, stability and robustness to enhance the industrial …
improvement of process repeatability, stability and robustness to enhance the industrial …
Deep semi-supervised learning of dynamics for anomaly detection in laser powder bed fusion
Highly complex data streams from in-situ additive manufacturing (AM) monitoring systems
are becoming increasingly prevalent, yet finding physically actionable patterns remains a …
are becoming increasingly prevalent, yet finding physically actionable patterns remains a …
Real-time defect detection using online learning for laser metal deposition
Defect prevention and detection are very crucial for the quality improvement of additive
manufacturing (AM) processes. Timely identification of imperfections and flaws in the …
manufacturing (AM) processes. Timely identification of imperfections and flaws in the …
Dual process monitoring of metal-based additive manufacturing using tensor decomposition of thermal image streams
Additive manufacturing (AM) processes are subject to lower stability compared to their
traditional counterparts. The process inconsistency leads to anomalies in the build, which …
traditional counterparts. The process inconsistency leads to anomalies in the build, which …
Spatially weighted PCA for monitoring video image data with application to additive manufacturing
BM Colosimo, M Grasso - Journal of Quality Technology, 2018 - Taylor & Francis
Abstract Machine vision systems for in-line process monitoring in advanced manufacturing
applications have attracted an increasing interest in recent years. One major goal is to …
applications have attracted an increasing interest in recent years. One major goal is to …
Melt pool level flaw detection in laser hot wire directed energy deposition using a convolutional long short-term memory autoencoder
While additive manufacturing has seen rapid proliferation in recent years, process
monitoring and quality assurance methods capable of detecting common flaws have seen …
monitoring and quality assurance methods capable of detecting common flaws have seen …
Metal-based additive manufacturing condition monitoring: A review on machine learning based approaches
The metal-based additive manufacturing (MAM) processes have great potential in wide
industrial applications, for their capabilities in building dense metal parts with complex …
industrial applications, for their capabilities in building dense metal parts with complex …
A deep convolutional autoencoder-based approach for anomaly detection with industrial, non-images, 2-dimensional data: A semiconductor manufacturing case study
In manufacturing industries, it is of fundamental importance to detect anomalies in
production in order to meet the required quality goals and to limit the number of defective …
production in order to meet the required quality goals and to limit the number of defective …
Automated anomaly detection of laser-based additive manufacturing using melt pool sparse representation and unsupervised learning
Advanced thermal imaging is increasingly invested in direct energy deposition (DED)
additive manufacturing (AM) to cope with information visibility of melt pool and tackle …
additive manufacturing (AM) to cope with information visibility of melt pool and tackle …