Abstract
Abstract This innovation represents a significant advancement in enhancing processing efficiency when dealing with engineering drawings. Traditionally, the review of customer drawings needs to be executed by experienced experts before manufacture. The identification and labelling of key features were reliant on human intervention for subsequent Design for Manufacturability (DFM) or G-code programming. However, the previous method not only consumed valuable time but also introduced the potential for human errors. In this context, we introduce a high-efficiency technology for recognizing engineering drawings, automatically labelling key features, and converting unstructured data into structured data. It is noteworthy that this technology distinguishes itself from traditional methods, such as R-CNN or similar neural network approaches and differs from pre-labeled engineering drawings reliant on experts manually inputting keywords for dimensions or layers. This work is a vital step towards the realization of intelligent manufacturing. For instance, our customers can now review engineering drawings online and receive immediate feedback. This online interaction is facilitated by processing structured data, a direct output of this presented technology, with other specific modules. Furthermore, the structured data seamlessly integrates into subsequent manufacturing procedures, including notifying the supply chain, generating 3D drawings, and CNC programming. In conclusion, this technology showcases its significance in advancing our vision of intelligent manufacturing at ZY Corp.
Published Version
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