Predictive Maintenance

End-to-end digitisation of physical assets within a value chain and their integration into a digital ecosystem is the focus of the fourth industrial revolution [1]. Ubiquitous sensors and microprocessors installed on machines, embedded systems and smart devices along with the increasing horizontal and vertical networking of value chains will result in unprecedently seen amounts of data.

The application of analytics techniques to this massively growing data flow can generate substantial benefits as valuable information can be quickly extracted and used to achieve in-depth understanding, gain insights and make discoveries for accurate, evidence-based and potentially autonomous decision making in complex industrial processes [2]. The most cited advantages that analytics can generate in the manufacturing world are related to maintenance operations. Maintenance is no longer seen as a non-value-added function that merely reduces machines availability; the current view is towards considering it as a source of added value, with the potential of driving performance improvements [3].