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Adhesive Selection via an Interactive, User-friendly System based on Symbolic AI

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Adhesive joints are increasingly used in industry for a wide variety of applications because of their favorable characteristics such as high strength-to-weight ratio, design flexibility, limited stress concentrations, planar force transfer, good damage tolerance and fatigue resistance. Selection of a proper adhesive for a particular application depends on many often conflicting product and manufacturing process requirements and is therefore a cumbersome task. Traditionally, adhesive selection is done by an adhesive expert based on experience, prior knowledge and trial and error. Adequate tooling to support adhesive bonding experts in the design processes is lacking, generally yielding suboptimal results. This research presents an interactive adhesive selector tool, aimed at supporting the design of adhesive joints. Knowledge on the gluing process and its associated constraints is captured from adhesive experts and represented formally in a Knowledge Base (KB). The knowledge inside the KB is then processed using the Imperative Declarative Programming (IDP) reasoning engine in order to support the adhesive selection. Through an intelligible, interactive, interface the application requirements (such as use conditions, materials, process requirements, etc.) are entered, based on which the IDP system reduces the search space of potential adhesives. The selector tool has been tested on an industrially relevant case in which an adhesive had to be selected for bonding a composite panel to a steel frame for an automotive application. Using the selector tool, an adhesive expert was able to select an appropriate adhesive 10 times faster than without.
Tijdschrift: Procedia CIRP
ISSN: 2212-8271
Volume: 109
Pagina's: 161 - 166
Jaar van publicatie:2022
Toegankelijkheid:Open