DAXONET AI FRONTIER
AI-Predictive Maintenance
Fix the problem before it breaks your production line. Our Motor Predictive Maintenance System uses plug-and-play IoT sensors to monitor your critical assets 24/7.
Why AI-Predictive Maintenance
Move from reactive firefighting to proactive precision. Our AI analyses machine health continuously so you can prevent failures before they happen.
Continuous Condition Monitoring
Industrial IoT sensors capture live data from machinery, such as vibration, temperature, acoustics, and pressure. AI systems process this “heartbeat” of the machine 24/7, providing a far more accurate picture of equipment health than manual inspections or periodic checks ever could.
Anomaly Detection & Failure Forecasting
Machine learning algorithms compare current sensor data against historical patterns to spot “invisible” signs of wear. The AI can identify subtle deviations—like a specific vibration frequency—to estimate the “Remaining Useful Life” (RUL) of a component.
Optimized Maintenance Scheduling
Instead of following a rigid calendar (preventive), AI Predictive Maintenance allows manufacturers to schedule repairs during planned downtime, ensure spare parts are ready in advance, and avoid the high costs of emergency fixes and lost production.
24/7
Continuous asset monitoring
60%
Less unplanned downtime
40%
Reduction in maintenance costs
3×
Longer equipment lifespan
CASE STUDY
The AGV Supplier
How we helped an Automated Guided Vehicle supplier predict motor failures weeks in advance using IoT sensors and AI digital twin technology.
Multi-Sensor Data Collection
Each AGV was equipped with compact IoT sensors to monitor motor vibration, operating temperature, and current draw (amperage) in real-time.
Digital Twin & Anomaly Detection
An AI model created a “digital twin” of a healthy motor. By comparing live data to this model, the AI could detect “micro-vibrations” and heat spikes that indicate bearing wear or winding insulation breakdown weeks before a failure.
Downtime Estimation
Identify the health status of critical components and identify root cause of failure via historical data behaviours. Predict the lifespan of the machines so that maintenance can be scheduled accordingly.
System screenshots
Stop Reacting. Start Predicting.
Let’s discuss how AI-Predictive Maintenance can reduce your downtime, extend equipment life, and cut maintenance costs.