Logo des Repositoriums
 

Towards Designing a User-centric Decision Support System for Predictive Maintenance in SMEs

Kurzanzeige
dc.contributor.authorKellner, Domenic
dc.contributor.authorLowin, Maximilian
dc.contributor.authorvon Zahn, Moritz
dc.contributor.authorChen, Johannes
dc.date.accessioned2021-12-14T10:56:55Z
dc.date.available2021-12-14T10:56:55Z
dc.date.issued2021
dc.description.abstractIn manufacturing, small and medium-sized enterprises (SMEs) face global competition. In the field of predictive maintenance (PdM), artificial intelligence (AI) helps to prevent machine failures and has the potential to significantly reduce costs and increase process efficiency. Even though PdM has several benefits, it also entails considerable challenges for SMEs, especially when it comes to user interactions. In this short paper, we harness the design science methodology and discuss several problems regarding user interactions with predictive maintenance applications. We incorporate two different literature streams, namely, predictive maintenance and decision support systems. Finally, we present necessary design requirements, principles, features, and propose a research design to further develop and evaluate a user-centric PdM decision support system. Thereby, we contribute to making AI tangible in SMEs.en
dc.identifier.doi10.18420/informatik2021-104
dc.identifier.isbn978-3-88579-708-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/37608
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofINFORMATIK 2021
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-314
dc.subjectpredictive maintenance
dc.subjectmachine learning
dc.subjectdecision support systems
dc.subjectdesign science research
dc.subjectexplainable artificial intelligence
dc.titleTowards Designing a User-centric Decision Support System for Predictive Maintenance in SMEsen
gi.citation.endPage1260
gi.citation.startPage1255
gi.conference.date27. September - 1. Oktober 2021
gi.conference.locationBerlin
gi.conference.sessiontitleWorkshop: Künstliche Intelligenz für kleine und mittlere Unternehmen (KI-KMU 2021)

Dateien

Originalbündel
1 - 1 von 1
Vorschaubild
Name:
N1-10.pdf
Größe:
254.77 KB
Format:
Adobe Portable Document Format
Herunterladen

Sammlungen

P314 - INFORMATIK 2021 - Computer Science & Sustainability