Enabling condition-based maintenance decisions with proactive event-driven computing

Condition Based Maintenance (CBM) can take advantage of the emergence of Internet of Things (IoT) and the proactive event-driven computing paradigm for fully exploiting its capabilities by enabling proactive maintenance decisions ahead of time. In this paper, proactive event-driven computing is used as a lever in order to provide a holistic CBM approach along with an information system for generating proactive maintenance recommendations. Since the Detect and the Predict phases of the “Detect-Predict-Decide-Act” proactivity principle as applied to the CBM framework are well-studied fields in literature, the focus of the current research is on the Decide phase that is still an unexplored area. Therefore, in the context of this paper, the approach, contributing decision methods and technical specifications of an associated information system are defined and developed for this phase. The proposed approach is implemented in an information system, which is deployed and evaluated in the context of two real industrial scenarios in the area of oil and gas and automotive lighting equipment industries. The results of a comparative and a sensitivity evaluation analysis show that the proposed approach can enable industrial business transformation from a reactive to a proactive mode of operation, in order to eliminate maintenance-related losses and optimize business performance.