Case study: the implementation of a data-driven industrial analytics methodology and platform for smart manufacturing
Integrated, 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 Technolo...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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The Prognostics and Health Management Society
2016-12-01
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| Series: | International Journal of Prognostics and Health Management |
| Subjects: | |
| Online Access: | https://papers.phmsociety.org/index.php/ijphm/article/view/2414 |
| _version_ | 1818881911230038016 |
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| author | Peter O’Donovan Ken Bruton Dominic T.J. O’Sullivan |
| author_facet | Peter O’Donovan Ken Bruton Dominic T.J. O’Sullivan |
| author_sort | Peter O’Donovan |
| collection | DOAJ |
| description | Integrated, 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 large-scale Air Handling Unit (AHU). |
| first_indexed | 2024-12-19T15:09:23Z |
| format | Article |
| id | doaj.art-3b5053e883804164954bd714519f7a5e |
| institution | Directory Open Access Journal |
| issn | 2153-2648 2153-2648 |
| language | English |
| last_indexed | 2024-12-19T15:09:23Z |
| publishDate | 2016-12-01 |
| publisher | The Prognostics and Health Management Society |
| record_format | Article |
| series | International Journal of Prognostics and Health Management |
| spelling | doaj.art-3b5053e883804164954bd714519f7a5e2022-12-21T20:16:21ZengThe Prognostics and Health Management SocietyInternational Journal of Prognostics and Health Management2153-26482153-26482016-12-0173doi:10.36001/ijphm.2016.v7i3.2414Case study: the implementation of a data-driven industrial analytics methodology and platform for smart manufacturingPeter O’Donovan0Ken Bruton1Dominic T.J. O’Sullivan2IERG, University College Cork, IrelandIERG, University College Cork, IrelandIERG, University College Cork, IrelandIntegrated, 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 large-scale Air Handling Unit (AHU).https://papers.phmsociety.org/index.php/ijphm/article/view/2414energy efficiencybig datasmart manufacturingindustrial analyticsair handling unit |
| spellingShingle | Peter O’Donovan Ken Bruton Dominic T.J. O’Sullivan Case study: the implementation of a data-driven industrial analytics methodology and platform for smart manufacturing International Journal of Prognostics and Health Management energy efficiency big data smart manufacturing industrial analytics air handling unit |
| title | Case study: the implementation of a data-driven industrial analytics methodology and platform for smart manufacturing |
| title_full | Case study: the implementation of a data-driven industrial analytics methodology and platform for smart manufacturing |
| title_fullStr | Case study: the implementation of a data-driven industrial analytics methodology and platform for smart manufacturing |
| title_full_unstemmed | Case study: the implementation of a data-driven industrial analytics methodology and platform for smart manufacturing |
| title_short | Case study: the implementation of a data-driven industrial analytics methodology and platform for smart manufacturing |
| title_sort | case study the implementation of a data driven industrial analytics methodology and platform for smart manufacturing |
| topic | energy efficiency big data smart manufacturing industrial analytics air handling unit |
| url | https://papers.phmsociety.org/index.php/ijphm/article/view/2414 |
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