Continuous load and stress accelerate gearbox degradation
Industrial gearboxes are core components that transmit power in many kinds of equipment, such as conveyors, mixers, mills and production machinery.
A gearbox failure can lead to a shutdown of the whole production equipment and high repair cost, so it is important to find small warning signs early and maintain at the right time.
Power signals of the motor driving the gearbox are monitored continuously at the electrical panel and analyzed with edge AI, so you can check changes in gearbox condition in real time and prevent unexpected failures.
Gearboxes operate under continuous load and mechanical stress.
As operating hours increase, problems such as bearing wear, gear damage, lubrication degradation and overheating can develop gradually.
These abnormalities often are not obvious at an early stage, so periodic inspection or time-based maintenance alone makes it hard to find them in time.
When a gearbox develops an abnormality, it can appear as a change in the load and power pattern of the drive motor, so it can be checked without attaching a sensor to the gearbox.
Key operating challenges
Unplanned downtime
A sudden gearbox failure can stop the entire production line.
High maintenance cost
Emergency repairs and part replacement after a failure raise maintenance cost.
Lack of real-time visibility
It is hard to follow changes in gearbox condition that occur between periodic inspections.
Shorter equipment life
If wear and inefficient operation are not found early, gearbox life can be shortened.
Hard to detect early abnormalities
Early abnormalities such as abnormal vibration or temperature change are hard to find by visual inspection alone.
Analyze changes in gearbox condition in real time
Power signals such as voltage and current of the motor driving the gearbox are collected and analyzed continuously to see changes in equipment condition in real time.
Panel-mounted measurement, edge AI analysis, communication and a dashboard are combined into one system, so you can grasp early signs quickly and turn them into actual maintenance action.
Real-time condition monitoring
Power signals and load data of the gearbox drive are collected continuously to track changes in equipment condition.
Edge AI abnormality detection
Collected data is analyzed on site to quickly detect abnormal conditions and potential signs of failure.
AI-based abnormality analysis
AI and machine learning analyze data trends and patterns to reveal early signs of failure such as wear, misalignment and load abnormalities.
Real-time abnormality alerts
When a sign of abnormality is confirmed, maintenance staff are alerted in real time so they can inspect and act before a failure occurs.
Centralized asset visibility
A dashboard shows the current condition, past operating trend and performance data of many gearboxes in one place.
Monitoring that scales across the plant
Start with a single unit and extend to a central server or cloud, widening monitoring from a single gearbox to a whole plant or multiple sites.
From repair after failure to condition-based maintenance
Applying condition diagnosis to industrial gearboxes lets you move from responding after a failure to performing maintenance at the right time, based on actual equipment condition.
Expected benefits
Fewer unplanned shutdowns
Early detection of gearbox abnormalities prevents sudden equipment shutdowns.
Lower maintenance cost
Planned maintenance based on equipment condition reduces emergency repairs and unnecessary part replacement.
Higher reliability and availability
Continuously managing gearbox condition supports stable operation of the production line.
Longer gearbox life
Finding and acting on abnormal conditions before they become serious damage extends equipment life.
Better operational visibility
Using real-time and historical data together lets you manage gearbox condition and performance changes more systematically.
Find small abnormalities first and prevent major failures
Most gearbox abnormalities do not start suddenly. They start from small changes such as wear, vibration change, temperature rise and lubrication degradation.
With continuous condition monitoring and edge AI analysis, you detect early signs of these changes and maintain at the right time, reducing unplanned downtime and maintenance cost and building a stable production environment.
Prove it on one asset first
A pilot starts with one critical asset, establishes its baseline and reviews edgeSV diagnostic results with your team.