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Big data collection and analysis for manufacturing organisations
Indian Institute of Technology Dehli, India.
University of Sunderland, UK.
Linnaeus University, Faculty of Technology, Department of Informatics. (Informatics)ORCID iD: 0000-0001-7048-8089
VTT Technical Research Centre of Finland, Finland.
2017 (English)In: Big Data and Information Analytics, ISSN 2380-6966, Vol. 2, no 2, p. 127-139Article in journal (Refereed) Published
Abstract [en]

Data mining applications are becoming increasingly important for the wide range of manufacturing and maintenance processes. During daily operations, large amounts of data are generated. This large volume and variety of data, arriving at a greater velocity has its own advantages and disadvantages. On the negative side, the abundance of data often impedes the ability to extract useful knowledge. In addition, the large amounts of data stored in often unconnected databases make it impractical to manually analyse for valuable decision-making information. However, an advent of new generation big data analytical tools has started to provide large scale benefits for the organizations. The paper examines the possible data inputs from machines, people and organizations that can be analysed for maintenance. Further, the role of big data within maintenance is explained and how, if not managed correctly, big data can create problems rather than provide solutions. The paper highlights the need to have advanced mining techniques to enable conversion of data into information in an acceptable time frame and to have modern analytical tools to extract value from the big datasets.

Place, publisher, year, edition, pages
American Institute of Mathematical Sciences, 2017. Vol. 2, no 2, p. 127-139
Keyword [en]
Big data, CBM, manufacturing
National Category
Computer and Information Sciences
Research subject
Computer and Information Sciences Computer Science
Identifiers
URN: urn:nbn:se:lnu:diva-68769DOI: 10.3934/bdia.2017002OAI: oai:DiVA.org:lnu-68769DiVA: diva2:1157479
Available from: 2017-11-16 Created: 2017-11-16 Last updated: 2018-01-13Bibliographically approved

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Campos, Jaime

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  • apa
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  • en-US
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  • nn-NB
  • sv-SE
  • Other locale
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Output format
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