IAMM: A maturity model for measuring industrial analytics capabilities in large-scale manufacturing facilities

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dc.contributor.author O'Donovan, Peter
dc.contributor.author Bruton, Ken
dc.contributor.author O'Sullivan, Dominic T. J.
dc.date.accessioned 2018-02-06T13:36:29Z
dc.date.available 2018-02-06T13:36:29Z
dc.date.issued 2016
dc.identifier.citation O’Donovan, P., Bruton, K. and O’Sullivan, D. T. J. (2016) 'IAMM: a maturity model for measuring industrial analytics capabilities in large-scale manufacturing facilities', International Journal of Prognostics and Health Management, 7, 032, (11pp). en
dc.identifier.volume 7
dc.identifier.issn 2153-2648
dc.identifier.uri http://hdl.handle.net/10468/5396
dc.description.abstract Industrial big data analytics is an emerging multidisciplinary field, which incorporates aspects of engineering, statistics and computing, to produce data-driven insights that can enhance operational efficiencies, and produce knowledgebased competitive advantages. Developing industrial big data analytics capabilities is an ongoing process, whereby facilities continuously refine collaborations, workflows and processes to improve operational insights. Such activities should be guided by formal measurement methods, to strategically identify areas for improvement, demonstrate the impact of analytics initiatives, as well as deriving benchmarks across facilities and departments. This research presents a formal multi-dimensional maturity model for approximating industrial analytics capabilities, and demonstrates the model’s ability to assess the impact of an initiative undertaken in a real-world facility. en
dc.description.sponsorship Irish Research Council/ Enterprise Ireland (EPSPG/2013/578) en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher PHM Society en
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.uri https://creativecommons.org/licenses/by/3.0/
dc.subject Engineering en
dc.subject Statistics en
dc.subject Computing en
dc.subject Industrial analytics en
dc.subject Multi-dimensional maturity model en
dc.title IAMM: A maturity model for measuring industrial analytics capabilities in large-scale manufacturing facilities en
dc.type Article (peer-reviewed) en
dc.internal.authorcontactother peter_odonovan@umail.ucc.ie en
dc.internal.availability Full text available en
dc.description.version Published Version en
dc.contributor.funder Irish Research Council
dc.contributor.funder Enterprise Ireland
dc.contributor.funder DePuy Synthes Spine
dc.description.status Peer reviewed en
dc.identifier.journaltitle International Journal of Prognostics and Health Management en
dc.internal.IRISemailaddress Peter O’Donovan, Engineering, University College Cork, Cork, Ireland. +353-21-490-3000 Email: peter_odonovan@umail.ucc.ie en
dc.identifier.articleid 32


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© 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. Except where otherwise noted, this item's license is described as © 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.
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