A data-driven method for enhancing the image-based automatic inspection of IC wire bonding defects

• Published in: International journal of production research Vol. 59; no. 16; pp. 4779 - 4793
• Main Authors: Chen, Junlong, Zhang, Zijun, Wu, Feng
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis 18.08.2021; Taylor & Francis LLC
• Subjects: Algorithms; Artificial neural networks; automatic inspection; Bonding; Classification; Data mining; Defects; Feature extraction; Image enhancement; Image segmentation; Inspection; Integrated circuits; intelligent manufacturing; Semiconductors; Wire; wire bonding quality; X-ray images

Visually inspecting integrated circuit (IC) wire bonding defects is important to ensuring the product quality after the packaging process. The availability of IC X-ray images offers an unprecedented opportunity of studying the image-based automatic IC wire inspection. In this paper, a data-driven me...