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arXiv · 2103.13003

Industrial Machine Tool Component Surface Defect Dataset

Tobias Schlagenhauf·Magnus Landwehr·Juergen Fleischer
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Abstract

Using machine learning (ML) techniques in general and deep learning techniques in specific needs a certain amount of data often not available in large quantities in technical domains. The manual inspection of machine tool components and the manual end-of-line check of products are labor-intensive tasks in industrial applications that companies often want to automate. To automate classification processes and develop reliable and robust machine learning-based classification and wear prognostics models, one needs real-world datasets to train and test the models. The dataset is available under https://doi.org/10.5445/IR/1000129520.

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Tobias Schlagenhauf, Magnus Landwehr, Juergen Fleischer. 2021-03-24. Industrial Machine Tool Component Surface Defect Dataset. https://doi.org/10.1016/j.dib.2021.107643

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