Feb. 12, 2024, 5:43 a.m. | Elke Schlager Andreas Windisch Lukas Hanna Thomas Kl\"unsner Elias Jan Hagendorfer Tamara Teppernegg

cs.LG updates on arXiv.org arxiv.org

Tool wear monitoring is crucial for quality control and cost reduction in manufacturing processes, of which drilling applications are one example. In this paper, we present a U-Net based semantic image segmentation pipeline, deployed on microscopy images of cutting inserts, for the purpose of wear detection. The wear area is differentiated in two different types, resulting in a multiclass classification problem. Joining the two wear types in one general wear class, on the other hand, allows the problem to be …

applications augmentation control cost cs.ai cs.cv cs.lg data detection evaluation example functions image images loss manufacturing microscopy monitoring paper pipeline processes quality segmentation semantic tool

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