Applications of Big Data analytics and Related Technologies in Maintenance—Literature-Based Research
Jens Baum 
1
Department of Economics, University of Applied Sciences Zwickau, 08012 Zwickau, Germany
2
Department of Industrial and Materials Science, Chalmers University of Technology, 41296 Gothenburg, Sweden
*
Author to whom correspondence should be addressed.
Machines 2018, 6(4), 54; https://doi.org/10.3390/machines6040054
Received: 9 August 2018 / Revised: 23 October 2018 / Accepted: 24 October 2018 / Published: 1 November 2018
(This article belongs to the Special Issue Smart Manufacturing, Digital Supply Chains and Industry 4.0)
Digitalisation is argued to increase the efficiency of maintenance activities in a production system. One consequence of digitalisation is data deluge; this allows data analytics methods and technologies to be used. However, the actual data analytical methods and technologies used may differ, thus leading to many scientific papers on this topic. The purpose of our contribution is to find and cluster scientific papers regarding the implemented approaches relevant for use in production maintenance. Our research is based on a broad, systematic literature review consisting of a two-step search approach combined with additional filtering and classification. Based on the search results, we evaluate and visualise the potential impact of data analytics on the subject of maintenance. The results of this study broadly summarise the research activities in production maintenance, whilst indicating that the impact of data analytics will grow further. Specific methodological approaches are clearly favored.
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Keywords:
maintenance; data analytics; big data; production systems; manufacturing systems
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MDPI and ACS Style
Baum, J.; Laroque, C.; Oeser, B.; Skoogh, A.; Subramaniyan, M. Applications of Big Data analytics and Related Technologies in Maintenance—Literature-Based Research. Machines 2018, 6, 54.
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