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NLP for product safety risk assessment

  • Recent developments in the area of Natural Language Processing (NLP) increasingly allow for the extension of such techniques to hitherto unidentified areas of application. This paper deals with the application of state-of-the-art NLP techniques to the domain of Product Safety Risk Assessment (PSRA). PSRA is concerned with the quantification of the risks a user is exposed to during product use. The use case arises from an important process of maintaining due diligence towards the customers of the company OMICRON electronics GmbH. The paper proposes an approach to evaluate the consistency of human-made risk assessments that are proposed by potentially changing expert panels. Along the stages of this NLP-based approach, multiple insights into the PSRA process allow for an improved understanding of the related risk distribution within the product portfolio of the company. The findings aim at making the current process more transparent as well as at automating repetitive tasks. The results of this paper can be regarded as a first step to support domain experts in the risk assessment process.

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Author:Michael HellwigORCiD, Steffen Finck, Thomas Mootz, Andreas Ehe, Florian Rein
Parent Title (English):21st International Conference on Intelligent Systems Design and Applications (ISDA 2021). December 13–15 2021
Subtitle (English):Towards consistency evaluations of human expert panels
Publication Series:Lecture Notes in Networks and Systems (LNNS, volume 418)
Place of publication:Cham
Editor:Ajith Abraham, Niketa Gandhi, Thomas Hanne, Tzung-Pei Hong, Tatiane Nogueira Rios, Weiping Ding
Document Type:Conference Proceeding
Year of publication:2022
Release Date:2023/02/06
Tag:Machine Learning; Natural Language Processing; Product Safety Risk
Number of pages:10
First Page:266
Last Page:276
Organisationseinheit:Forschung / Forschungszentrum Business Informatics
Forschung / Josef Ressel Zentrum für Robuste Entscheidungen
DDC classes:000 Allgemeines, Informatik, Informationswissenschaft / 000 Allgemeines, Wissenschaft / 004 Informatik
JEL-Classification:L Industrial Organization
Open Access?:nein
Peer review:wiss. Beitrag, peer-reviewed
Publicationlist:Finck, Steffen
Hellwig, Michael