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

Industry 4.0 is the new digital industrial revolution, the one in which manufacturing processes are enhanced by the 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 seen as 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. 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.