Deep learning and analytical study of void regional formation in flip-chip underfilling process
Calvin Ling,
Muhammad Taufik Azahari,
Mohamad Aizat Abas
et al.
Abstract:Purpose
This paper aims to study the relationship between the ball grid array (BGA) flip-chip underfilling process parameter and its void formation region.
Design/methodology/approach
A set of top-down scanning acoustic microscope images of BGA underfill is collected and void labelled. The labelled images are trained with a convolutional neural network model, and the performance is evaluated. The model is tested with new images, and the void area with its region is analysed with its dispensing parameter.
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