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Towards Predictive Maintenance as a Service in the Smart Housing Industry

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dc.contributor.authorLowin, Maximilian
dc.contributor.authorMihale-Wilson, Cristina
dc.date.accessioned2021-12-14T10:57:54Z
dc.date.available2021-12-14T10:57:54Z
dc.date.issued2021
dc.description.abstractMaintenance is a significant cost driver in many industries with tangible assets. Aiming to predict damages before they occur, this paper focuses on predictive maintenance (PdM) for smart buildings and apartments – a multi-billion-dollar market with substantial cost savings potential. Based on stakeholder groups’ heterogeneity within the smart housing industry, PdM cannot be a one-fits-all solution. To be effective, practitioners can enrich PdM with Artificial Intelligence (AI). However, to match very heterogeneous environments and the various needs of the stakeholders, PdM must be modular and flexible. Motivated by the challenges and peculiarities for implementing Predictive Maintenance as a Service (PdMaaS) in the smart housing industry, we provide a concept to support managers to overview and optimize complex PdM needs in complex and heterogeneous environments.en
dc.identifier.doi10.18420/informatik2021-089
dc.identifier.isbn978-3-88579-708-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/37758
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofINFORMATIK 2021
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-314
dc.subjectsmart services
dc.subjectpredictive maintenance
dc.subjectsmart housing industry
dc.subjectvisualization
dc.titleTowards Predictive Maintenance as a Service in the Smart Housing Industryen
gi.citation.endPage1106
gi.citation.startPage1093
gi.conference.date27. September - 1. Oktober 2021
gi.conference.locationBerlin
gi.conference.sessiontitle13. Workshop {KI-basiertes} Management und Optimierung komplexer Systeme (MOC 2021)

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P314 - INFORMATIK 2021 - Computer Science & Sustainability