From in-situ monitoring toward high-throughput process control: cost-driven decision-making framework for laser-based additive manufacturing

• Published in: Journal of manufacturing systems Vol. 51; pp. 29 - 41
• Main Authors: Jafari-Marandi, Ruholla, Khanzadeh, Mojtaba, Tian, Wenmeng, Smith, Brian, Bian, Linkan
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.04.2019
• Subjects: Additive manufacturing (AM); Artificial neural networks (ANN); Porosity prediction; Self-organizing error-drive neural networks (SOEDNN); Thermal history; Additive manufacturing (AM); Artificial neural networks (ANN); Thermal history; Self-organizing error-drive neural networks (SOEDNN); Porosity prediction

•The paper presents an ANN-based cost-driven classification method for intelligent porosity detection.•The method accounts for spatial distribution of defects and recommends cost-wise smart corrective actions.•The method excels at porosity detection in regard to both accuracy and cost when compared...