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2022 | OriginalPaper | Buchkapitel

Knowledge-Based Support for Adhesive Selection

verfasst von : Simon Vandevelde, Jeroen Jordens, Bart Van Doninck, Maarten Witters, Joost Vennekens

Erschienen in: Logic Programming and Nonmonotonic Reasoning

Verlag: Springer International Publishing

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Abstract

This work presents a real-life application developed to assist adhesive experts in the selection of suitable adhesives. As the popularity of adhesive joints in industry increases, so does the need for tools to support the selection process. While such tools already exist, they are either too limited in scope, or offer too little flexibility in use. In this work, we first extract experts’ knowledge about this domain and formalize it in a Knowledge Base (KB). The IDP-Z3 reasoning system can then be used to derive the necessary functionality from this KB. Together with a user-friendly interactive interface, this creates an easy-to-use tool capable of assisting the adhesive experts. The experts are positive about the tool, stating that it will help save time and find more suitable adhesives.

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Metadaten
Titel
Knowledge-Based Support for Adhesive Selection
verfasst von
Simon Vandevelde
Jeroen Jordens
Bart Van Doninck
Maarten Witters
Joost Vennekens
Copyright-Jahr
2022
DOI
https://doi.org/10.1007/978-3-031-15707-3_34

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