Abstract
Rapid developments in technologies such as Robotics, Digital Automation, Internet of Things and AI have heralded the Fourth Industrial Revolution, commonly referred to as Industry 4.0 (i4.0). Industrial operations and products have since become more competitive and hence more demanding. Systems have also become more complex and inter-disciplinary in nature. Diligent surveillance of operating conditions of such systems and initiation of appropriate actions based on monitored conditions have become indispensable for sustainability of businesses. Significant amount of research is being undertaken world over to meet this requirement of the day. In line with the ongoing research, this paper highlights the need for identifying the needs of condition monitoring preparedness of process plants located in remote places, especially in a logistic sense. Issues related to assessment of the need for the new paradigm in condition monitoring, challenges faced by such plants in the transition from legacy systems to a new system and customisation and optimisation of Predictive Maintenance under Industry 4.0 (PdM 4.0) have been discussed. A Case Study pertaining to remote monitoring of a gas compressor system of a petroleum refinery in North Eastern India and a Case Discussion on Basic Technical Requirements for the implementation of Industrial internet of Things (IIOT) based predictive maintenance system are presented to highlight the benefits and issues associated with the radical shift in paradigm from legacy systems to Industry 4.0 based predictive maintenance (PdM 4.0) system. Frameworks for PdM 4.0 system decision making and development are also suggested for supporting future work in this area.
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Ramesh, P.G., Dutta, S.J., Neog, S.S., Baishya, P., Bezbaruah, I. (2020). Implementation of Predictive Maintenance Systems in Remotely Located Process Plants under Industry 4.0 Scenario. In: Karanki, D., Vinod, G., Ajit, S. (eds) Advances in RAMS Engineering. Springer Series in Reliability Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-36518-9_12
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