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[HTML][HTML] In-situ sensing, process monitoring and machine control in Laser Powder Bed Fusion: A review
Process monitoring and sensing is widely used across many industries for quality
assurance, and for increasing machine uptime and reliability. Though still in the emergent …
assurance, and for increasing machine uptime and reliability. Though still in the emergent …
A review on machine learning in 3D printing: applications, potential, and challenges
Additive manufacturing (AM) or 3D printing is growing rapidly in the manufacturing industry
and has gained a lot of attention from various fields owing to its ability to fabricate parts with …
and has gained a lot of attention from various fields owing to its ability to fabricate parts with …
[HTML][HTML] Machine learning-assisted in-situ adaptive strategies for the control of defects and anomalies in metal additive manufacturing
In metal additive manufacturing (AM), the material microstructure and part geometry are
formed incrementally. Consequently, the resulting part could be defect-and anomaly-free if …
formed incrementally. Consequently, the resulting part could be defect-and anomaly-free if …
In-situ measurement and monitoring methods for metal powder bed fusion: an updated review
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 …
processes, to support part and process qualification and for the early detection of anomalies …
On the application of in-situ monitoring systems and machine learning algorithms for develo** quality assurance platforms in laser powder bed fusion: A review
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 …
fabricate high-quality complex-shape components. This technology has significantly …
Deep learning-assisted real-time defect detection and closed-loop adjustment for additive manufacturing of continuous fiber-reinforced polymer composites
Real-time defect detection and closed-loop adjustment of additive manufacturing (AM) are
essential to ensure the quality of as-fabricated products, especially for carbon fiber …
essential to ensure the quality of as-fabricated products, especially for carbon fiber …
Layer-wise anomaly detection and classification for powder bed additive manufacturing processes: A machine-agnostic algorithm for real-time pixel-wise semantic …
Increasing industry acceptance of powder bed metal Additive Manufacturing requires
improved real-time detection and classification of anomalies. Many of these anomalies, such …
improved real-time detection and classification of anomalies. Many of these anomalies, such …
In-Process monitoring of porosity during laser additive manufacturing process
This paper describes a deep-learning-based method for porosity monitoring in laser additive
manufacturing process. A high-speed digital camera was mounted coaxially to the process …
manufacturing process. A high-speed digital camera was mounted coaxially to the process …
Machine learning for advanced additive manufacturing
Increasing demand for the fabrication of components with complex designs has spurred a
revolution in manufacturing methods. Additive manufacturing stands out as a promising …
revolution in manufacturing methods. Additive manufacturing stands out as a promising …
Process modeling in laser powder bed fusion towards defect detection and quality control via machine learning: The state-of-the-art and research challenges
In recent years, machine learning (ML) techniques have been extensively investigated to
strengthen the understanding of the complex process dynamics underlying metal additive …
strengthen the understanding of the complex process dynamics underlying metal additive …