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Semantic Framework for Predictive Maintenance in a Cloud Environment
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0002-8906-630X
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. KTH Royal Institute of Technology, Stockholm, Sweden. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0001-8679-8049
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Produktion och Automatiseringsteknik, Production and Automation Engineering)ORCID iD: 0000-0002-4107-0991
2017 (English)In: 10th CIRP Conference on Intelligent Computation in Manufacturing Engineering - CIRP ICME '16 / [ed] Roberto Teti and Doriana M D'Addona, Elsevier, 2017, Vol. 62, 583-588 p.Conference paper, (Refereed)
Abstract [en]

Proper maintenance of manufacturing equipment is crucial to ensure productivity and product quality. To improve maintenance decision support, and enable prediction-as-a-service there is a need to provide the context required to differentiate between process and machine degradation. Correlating machine conditions with process and inspection data involves data integration of different types such as condition monitoring, inspection and process data. Moreover, data from a variety of sources can appear in different formats and with different sampling rates. This paper highlights those challenges and presents a semantic framework for data collection, synthesis and knowledge sharing in a Cloud environment for predictive maintenance.

Place, publisher, year, edition, pages
Elsevier, 2017. Vol. 62, 583-588 p.
Series
Procedia CIRP, ISSN 2212-8271 ; 62
Keyword [en]
Predictive maintenance, Knowledge management, Cloud manufacturing
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-13568DOI: 10.1016/j.procir.2016.06.047OAI: oai:DiVA.org:his-13568DiVA: diva2:1096893
Conference
10th CIRP Conference on Intelligent Computation in Manufacturing Engineering; CIRP ICME '16; Ischia; Italy; 20-22 July 2016
Available from: 2017-05-19 Created: 2017-05-19 Last updated: 2017-06-16

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Schmidt, BernardWang, LihuiGalar, Diego
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CiteExportLink to record
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Citation style
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