Case study: the implementation of a data-driven industrial analytics methodology and platform for smart manufacturing

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dc.contributor.authorO'Donovan, Peter
dc.contributor.authorBruton, Ken
dc.contributor.authorO'Sullivan, Dominic T. J.
dc.contributor.funderDePuy Synthes Spine
dc.contributor.funderIrish Research Council
dc.contributor.funderEnterprise Ireland
dc.date.accessioned2018-02-06T13:36:29Z
dc.date.available2018-02-06T13:36:29Z
dc.date.issued2016
dc.description.abstractIntegrated, real-time and open approaches relating to the development of industrial analytics capabilities are needed to support smart manufacturing. However, adopting industrial analytics can be challenging due to its multidisciplinary and cross-departmental (e.g. Operation and Information Technology) nature. These challenges stem from the significant effort needed to coordinate and manage teams and technologies in a connected enterprise. To address these challenges, this research presents a formal industrial analytics methodology that may be used to inform the development of industrial analytics capabilities. The methodology classifies operational teams that comprise the industrial analytics ecosystem, and presents a technology agnostic reference architecture to facilitate the industrial analytics lifecycle. Finally, the proposed methodology is demonstrated in a case study, where an industrial analytics platform is used to identify an operational issue in a largescale Air Handling Unit (AHU).en
dc.description.sponsorshipIrish Research Council/ Enterpise Ireland (EPSPG/2013/578)en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.articleid26
dc.identifier.citationO’Donovan, P., Bruton, K. and O’Sullivan, D. T. (2016) 'Case study: the implementation of a data-driven industrial analytics methodology and platform for smart manufacturing', International Journal of Prognostics and Health Management, 7,026, (22pp).en
dc.identifier.endpage22
dc.identifier.issn2153-2648
dc.identifier.journaltitleInternational Journal of Prognostics and Health Managementen
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/10468/5397
dc.identifier.volume7
dc.language.isoenen
dc.publisherPHM Societyen
dc.relation.urihttp://www.phmsociety.org/sites/phmsociety.org/files/phm_submission/2016/ijphm_16_026.pdf
dc.rights© 2016, Peter O’Donovan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 United States License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/
dc.subjectIndustrial analytics methodologyen
dc.subjectSmart manufacturingen
dc.titleCase study: the implementation of a data-driven industrial analytics methodology and platform for smart manufacturingen
dc.typeArticle (peer-reviewed)en
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