In-situ defect detection in laser-directed energy deposition with machine learning and multi-sensor fusion

• Main Authors: Chen, Lequn, Moon, Seung Ki
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Article
• Language: English
• Published: 2024
• Subjects: Engineering; Additive manufacturing; In-situ monitoring
• Online Access: https://hdl.handle.net/10356/180840
• Institution: Nanyang Technological University

Early defect identification in laser-directed energy deposition (L-DED) additive manufacturing (AM) is pivotal for preventing build failures. Traditional single-modal monitoring approaches lack the capability to fully comprehend process dynamics, leading to a gap in multisensor monitoring strategies...