Predictive Maintenance Using IoT in Oil Refinery Operations

Rizky Andrika

Abstract


Oil refineries face complex operational challenges due to the continuous demand for high throughput and the critical nature of their equipment. Predictive maintenance, powered by the Internet of Things (IoT), offers a proactive approach to managing refinery operations by monitoring equipment in real time and predicting failures before they occur. This paper explores the application of IoT sensors and data analytics in refinery maintenance, focusing on how predictive maintenance can improve operational efficiency, reduce downtime, and extend equipment life. Case studies highlight successful implementations, and the paper concludes with recommendations for further advancements in IoT-enabled predictive maintenance for refineries.

Keywords


predictive maintenance, IoT, oil refineries, operational efficiency.

References


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