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Collaborative Data Analytics for Industry 4.0:Challenges,Opportunities and Models

Author:
Lazarova-Molnar, Sanja  Mohamed, Nader  Al-Jaroodi, Jameela  


Journal:
2018 SIXTH INTERNATIONAL CONFERENCE ON ENTERPRISE SYSTEMS (ES 2018)


Issue Date:
2018


Abstract(summary):

Industry 4.0 is the adopted name for the new digital industrial revolution, the one in which manufacturing processes are enhanced by existing and developing Information and Communication Technologies (ICT). The highest portion of generated data stems from manufacturing. However, for a single manufacturing facility to benefit from its data, it needs a significant operation time. This is even truer for Small and Medium Enterprises (SMEs), who have been identified as a very weak link for embracing the new digital revolution. If manufacturing facilities collaborate and share data, which is then jointly analyzed, it could significantly enhance both feasibility and quality of data analytics processes, benefitting both large and small manufacturers. As a straightforward example, let us observe one of the key factors and performance metrics of manufacturing facilities, i.e. reliability and availability. The key events in this analysis of systems are faults and failures, which are both known to be rare events. Therefore, obtaining sufficient amount of data to build accurate fault models for a single machine or device would need long operation time that could be significantly shortened by joining data from more sources. There are also additional added benefits to this, such as the increased pressure for quality on factory machine manufacturers. In this paper we investigate the meaning of Collaborative Data Analytics (CDA) in the context of Industry 4.0, and identify potential models of performing it.


Page:
100---107


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