Big Data Collection and Analysis for Manufacturing Organisations

Pankaj Sharma (Corresponding Author), David Baglee, Jaime Campos, Erkki Jantunen

Research output: Contribution to journalArticleScientificpeer-review

Abstract

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 bene ts 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.
Original languageEnglish
Pages (from-to)127-139
JournalBig Data and Information Analytics
Volume2
Issue number2
DOIs
Publication statusPublished - 2017
MoE publication typeA1 Journal article-refereed

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Data mining
Decision making
Big data

Keywords

  • big data
  • CBM
  • manufacturing

Cite this

Sharma, Pankaj ; Baglee, David ; Campos, Jaime ; Jantunen, Erkki. / Big Data Collection and Analysis for Manufacturing Organisations. In: Big Data and Information Analytics. 2017 ; Vol. 2, No. 2. pp. 127-139.
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Big Data Collection and Analysis for Manufacturing Organisations. / Sharma, Pankaj (Corresponding Author); Baglee, David; Campos, Jaime; Jantunen, Erkki.

In: Big Data and Information Analytics, Vol. 2, No. 2, 2017, p. 127-139.

Research output: Contribution to journalArticleScientificpeer-review

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