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Based on AI analytics and cloud-connected equipment, KONE has developed a real-time analysis of operating data and operating conditions for escalators. Predictive escalator maintenance makes it possible to detect warning signs of failures or malfunctions, and thus trigger preventive interventions to avoid unnecessary repairs or downtime.
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- Handrail bearing failure or over-tensioning leading to increased handrail temperature.
- Misalignment or rust in the step band causing increasing noise levels.
- Increased braking distance or speed differences between the handrail and step band, signaling safety risks.
- Stoppages due to electrical system protection or foreign objects entrapped in the step band or comb plates.
- Instability in the drive station, detected through excessive vibration on the gearbox, or oil degradation indicated by rising temperatures.
- If you are experiencing any of these escalator issues, make sure to report them promtly as they are both safety risks and early indication of escalator breakdown."
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- Unusual noise levels generated by the step band or handrail.
- Changes in braking distance or speed inconsistencies.
- Elevated temperatures in key components such as the handrail or drive station.
- Vibration detected on the gearbox, indicating potential instability.
- Any deviations from standard operating parameters as monitored by predictive maintenance systems.
Escalator predictive maintenance uses sensors to track and gather actionable data on various escalator components and behaviors. By monitoring these indicators, potential issues can be identified early, enabling proactive escalator maintenance interventions to prevent escalator failures and ensure continued smooth and safe operation.