Wireless vibration monitoring on tank mixers
Using IoT-based wireless vibration sensors on refinery tank mixers enhances predictive maintenance and data analysis to improve operational efficiency
Murat Barış Türkoğlu and Mert Uztemur Tüpraş
I n the global energy and refining sectors, digital trans - formation is reshaping maintenance strategies by inte - grating smart technologies that enhance asset reliability, reduce operational costs, and improve safety. Among these technologies, the Internet of Things (IoT) has emerged as a cornerstone for enabling predictive maintenance, par - ticularly for rotating equipment that is critical to process continuity. In addition to vibration sensors at the Tüpraş Izmir Refinery, wireless technologies are utilised for various parameters, such as pressure, temperature, valve position, flow, and steam detection. Tank mixer motors, which operate continuously in refin - ery environments, are prone to mechanical degradation and failure. Such failures can lead to costly downtime, safety hazards, and production losses. To mitigate these risks, this study introduces a refinery-deployed wireless vibration monitoring system that leverages an IoT-based architec - ture to enable real-time condition tracking and proactive maintenance planning. The system utilises industrial-grade wireless vibration sensors to collect three-axis vibration and temperature data from mixer motors. These sensors communicate via the WirelessHART protocol, ensuring secure and reliable data transmission in complex industrial networks. The data is routed through a multi-layered architecture involving WirelessHART gateways, OPC servers in demilitarised zones (DMZs), and process historian databases (PHDs), which sup - port long-term trend analysis and real-time alerting. During the deployment period, the system successfully identified abnormal vibration patterns in three separate units, allowing maintenance teams to intervene before failures occurred. These interventions included bearing replacements, mechanical realignments, and emergency shutdowns, all of which were executed based on early warnings generated by the system. The results demon - strate the effectiveness of wireless monitoring in reducing reactive maintenance, optimising resource allocation, and improving equipment reliability. This study not only validates the technical feasibility of wireless vibration monitoring in refinery settings but also highlights its strategic value in building scalable, data- driven predictive maintenance frameworks. The approach sets a precedent for expanding similar systems to other
rotating assets, such as pumps, compressors, and fans, thereby contributing to the broader digitalisation of indus - trial maintenance operations. Predictive maintenance In industrial operations, unplanned equipment failures can lead to severe production interruptions, increased mainte - nance expenses, and, in some cases, safety and environ - mental risks. These disruptions not only affect immediate output but can also have cascading effects on supply chains, regulatory compliance, and workforce productivity. For example, a single motor failure in a tank mixer can halt an entire batch process, delay downstream operations, and potentially cause contractual penalties due to missed deliv - ery timelines. Additionally, emergency repairs often require expedited parts and overtime labour, further inflating costs. These challenges have prompted the transition from tra - ditional preventive maintenance approaches, which rely on fixed schedules and historical averages, to predictive main - tenance strategies supported by real-time monitoring tech - nologies. Predictive maintenance enables organisations to anticipate failures before they occur, allowing for targeted interventions that minimise downtime and extend equip - ment lifespan. As part of this transformation, the deployment of wire - less vibration sensors has played a pivotal role in enhanc - ing visibility into the mechanical behaviour of tank mixer motors. The vibration sensor is a rugged, field-proven sensor designed for harsh industrial environments. It cap - tures three-axis vibration data along with temperature measurements, providing a comprehensive view of equip - ment health. Its wireless communication is based on the WirelessHART protocol, which ensures reliable and secure data transmission even in complex refinery infrastructures. The sensors are mounted directly onto mixer motor housings and configured to transmit data at regular inter - vals. This eliminates the need for manual data collection and enables continuous condition monitoring. The data is received by a WirelessHART gateway, which acts as a bridge between field devices and higher-level control sys - tems. From there, the data flows through an OPC server located in a secure DMZ, eventually reaching the PHD for long-term storage and analysis.
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PTQ Q1 2026
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