We were approached by an industrial client whose production lines relied heavily on cooling systems to remain operational. A failure in the cooling system had previously caused significant downtime, resulting in costly disruptions lasting one or two days. They sought our expertise to implement an AI-based predictive maintenance system that could detect potential cooling system issues before they led to failures.
Key Challenge:
The main source of problems was identified as the cooling fan. When the fan malfunctioned, it often led to further damage to surrounding components, such as the shaft, exacerbating the downtime and repair costs.
Our Solution:
- Sensor Deployment: We installed vibration and audio sensors to monitor the cooling system in real time. These sensors continuously collected data on the fan and other critical components, providing insights into their operating conditions.
- AI Model Development: Using the sensor data, we trained a deep neural network to identify patterns indicative of potential faults. The system learned to classify different types of faults and conditions, such as abnormal vibrations or unusual sounds, that often precede fan failures or shaft damage.
- Fault Detection and Alert System: The AI-powered system was integrated with a central monitoring console that analyzed the data in real time. When the system detected a high probability of an impending failure, it sent alerts to the operations team, enabling them to take preemptive action.
- Protective Engine Reporting: The predictive maintenance system was designed to communicate directly with the protective engine, ensuring that critical alerts were acted upon immediately, reducing the risk of a complete system failure.
Impact and Results:
By deploying this AI-based predictive maintenance solution, the client was able to proactively address cooling system issues before they escalated into costly failures. The early detection of potential fan malfunctions prevented further damage to neighboring components and drastically reduced downtime. This system not only improved operational efficiency but also minimized maintenance costs and extended the lifespan of the cooling system components.
;)
