Many of the high rise buildings, offices, hospitals, hotels, auditoriums, and other facilities globally are partially or fully shut due to the ongoing pandemic and facilities management has challenges in ensuring the uptime through timely tracking of repairs and monitoring of preventive maintenance schedules, as the lockdown rules are relaxed. Here is a solution that will help in remotely tracking and monitoring of high value and critical production equipment.
Anomaly detection (or outlier detection) is the identification of rare items, events, or observations that raise suspicions by differing significantly from the majority of the data captured using noninvasive indoor location tracking and monitoring devices attached to industrial equipment.
Tracking repairs, monitoring preventive maintenance
- The group tracking solutions enhances proactive maintenance through just in time responses to machine faults and process deterioration.
- With the use of remote access to the operational condition, it benefits not only efficient manpower but also helps in decision making.
- Indoor location tracking devices reduces the downtime of the equipment, avoiding delayed breakdown notifications
- Mainly two parameters employ for remote monitoring of temperature, pressure, location and G-force.
- Suitable sensors are interfaced with network enabled microcontrollers installed in the elevator system that can be utilized to monitor remotely if any deterioration in its working condition.
- The microcontroller works as the control unit, carrying out some logical reasoning and arithmetic on the read sensor data for preventive maintenance decision-making.
- The intelligent ability of the microcontroller to carry out the logical operation of the read values against a predetermined severity condition level of the system while using its IoT capability in sending the data and notifications in the event of an abnormality in the system.
- Unlike reactive maintenance, where actions are taken whenever a system failure occurs, on-condition monitoring maintenance checks the condition of the system against the limit threshold, which is the severity limit of each condition of the machine.
- The limits are determined by the elevator manufacturer or through machine data learning algorithms.
- According to the manufacturer’s data from vendors such as Schindler and Otis, the study states that the vibration of the elevator car should be ±5mg to its mean vibration; therefore, the condition of the system based on vibration is diagnosed for anomaly detection.