Concrete

Condition-based maintenance avoids over-servicing

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JayaKrishna Kokku, Lead – Technical Operations, APAC & Middle East, Nanoprecise Sci Corp shares how their AI-powered IoT solution boosts productivity and sustainability in dusty cement plants through predictive maintenance. Read the full interview to learn more.

In an industry where dust, heat and vibration constantly challenge the health of critical equipment, predictive maintenance is fast becoming a game-changer. In this conversation, JayaKrishna Kokku, Lead – Technical Operations, APAC & Middle East, explains how Nanoprecise’s IoT solution is tackling the harsh realities of cement environments, delivering real-time equipment insights, accurate Remaining Useful Life (RUL) predictions and ensuring longer asset life and fewer costly breakdowns.

How does Nanoprecise IoT solution tackle equipment monitoring challenges in dusty cement plant environments?
Its wireless sensors are rugged, IP68 rated, and can reliably operate in high-dust environments without degradation. These sensors continuously monitor vibration, temperature, acoustic signals, humidity, Magnetic flux and RPM on critical rotating equipment. Data is transmitted securely to the cloud, enabling continuous, remote asset health monitoring, even in areas difficult for human inspection.

What role does your AI-driven analytics platform play in improving operational efficiency in cement plants?
The AI-driven analytics platform from Nanoprecise processes sensor data using advanced machine learning and physics-based algorithms. It detects early signs of component degradation (e.g., bearing faults, misalignment, imbalance) and provides actionable insights. By identifying potential failures weeks or months in advance, the platform allows cement plant operators to shift from reactive to proactive maintenance.

How do accurate RUL (Remaining Useful Life) insights help cement manufacturers optimise maintenance and reduce downtime?
Nanoprecise RUL predictions are powered by AI models that analyse sensor data fault trends over time. By accurately forecasting how long a component or system will function before failure, maintenance teams can plan interventions only, when necessary, rather than on fixed schedules. This minimises unnecessary maintenance, avoids catastrophic breakdowns, and ensures spare parts and labour are optimally allocated—drastically reducing both planned and unplanned downtime.

Can predictive maintenance be using your technology boost productivity while lowering operational disruptions?
Absolutely! Predictive maintenance enabled by Nanoprecise technology provides early fault detection and automated diagnostics, ensuring that equipment is always in optimal working condition. By addressing issues before they escalate, plants can maintain continuous operations, increase equipment uptime, and reduce the risk of costly shutdowns.

How does your solution support both productivity and sustainability goals in cement manufacturing?

  • Reduced Energy Waste: Equipment running inefficiently consumes more energy. Early detection of faults ensures machines run optimally, reducing unnecessary energy usage.
  • Lower Carbon Emissions: Improved efficiency and reduced downtime mean lower emissions per ton of cement produced.
  • Extended Equipment Life: Condition-based maintenance avoids over-servicing, extending the life of components and reducing waste.

Together, these benefits support sustainable operations without compromising output.

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