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Abstract: The increasing variety of products has resulted in a rise in production errors, primarily due to more complexity in manufacturing processes. This paper proposes a data-driven inline ...

Abstract: The development of graph neural networks has been driven by the widespread area of applications where graphs are naturally fit and by the advances in making solutions scalable. When it comes ...