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VERSION:2.0
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ORGANIZER;CN=ESTAD 2023:mailto:info@metec-estad.com
LOCATION:Room 1
SUMMARY:Use of robust deep learning methods for the automatic quality assessment of steel products
DESCRIPTION:Growing customer expectations together with increasing availability of relevant information and high flexibility of final product features are taking established Decision Support Systems (DSS) performing automatic release decisions continuously to their limits. Emerging machine-learning technologies could solve this problem, but concepts for their robust industrial application performing high-stakes decisions are missing.
This paper aims to report our attempt to improve the automatic quality assessment of steel products by means of a holistic approach combining deep learning technology with sophisticated management of underlying training data to enable the optimal use of all available data sources and simultaneously simplify the configurability and maintainability of previous DSS.

CLASS:PUBLIC
DTSTART:20230615T141000
DTEND:20230615T143000
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