Jake Lee, Principal Engineer and Head of the Machine Learning Group at Samsung, presents the “Image-Based Deep Learning for Manufacturing Fault Condition Detection” tutorial at the September 2020 Embedded Vision Summit.

In this presentation, Lee explores applying deep learning to analyzing manufacturing parameter data to detect fault conditions. The manufacturing parameter data contains multivariate time series sensor signals from a fabrication line. Due to practical manufacturing limitations, datasets are often incomplete, imbalanced and/or not well-formed for deep learning models. To overcome these challenges, Samsung applies new data augmentation methods to train a deep CNN for fault condition classification using deep generative models.

Lee also proposes an efficient method to convert multiple time series sensor inputs into a two-dimensional image representation to enable the use of image-based CNNs. Samsung’s experiment results show the fault classification accuracy improvement obtained by applying these techniques.

See here for a PDF of the slides.

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