Remaining Useful Life Prediction with IoT & AI avoids Catastrophic Failure




Gearbox & motor assembly [Critical]

Fault Predicted

Remaining Useful Life

"See how Edmonton International Airport benefited from our RotationLF platform and achieved major cost savings in thousands of dollars by detecting and replacing a bearing during a regular maintenance shutdown. Our solution also included wireless sensors that significantly reduced unplanned downtime on EIA’s baggage handling system."

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A predictive approach to the maintenance of the baggage system avoided the unplanned downtime. Placement of wireless RotationLF sensors on the drive motor and on the input and output shafts of each gearbox allowed continuous real-time monitoring for early stage fault detection. The secure WiFi-enabled sensors uploaded the vibration, acoustic emission, temperature & humidity data to the Cloud. Our Articial Intelligence algorithms analyzed this data and give results in the form of a dashboard

On one of the gearboxes & motor drives, a bearing inner race fault was detected in the drive motor within the rst week of monitoring. The deterioration of the bearing was tracked and within a short period of time. Faults on bearing outer race, ball and cage were also detected.


RotationLF accurately diagnosed the leading fault on gearbox & motor assembly and predicted the time within which the failure can happen and alerted the airport officials 250 hours in advance. When the Remaining Useful Life determined by RotationLF dropped to a critical level, the maintenance staff changed out the motor during a regularly scheduled shutdown. On disassembly, the root cause of the fault was found to be severe pitting on each ball in the non-drive end bearing.

Burn marks on the outer race indicated that the bearing was nearing catastrophic failure. The RUL prediction provided sufficient time to schedule the motor repair during a regularly planned maintenance outage. The vibration amplitude depicted in the above plot drops significantly once the bearing is replaced, confirming the findings of the RotationLF system.


Nanoprecise specializes in the implementation of Artificial Intelligence and IoT technology for predictive asset maintenance and condition monitoring. Our timely and accurate diagnosis of machine faults provides our clients insights that allow them to make decisions that will save them considerable time and resources. Nanoprecise is headquartered in Edmonton, Canada with branches in Bangalore, India; San Diego, USA, and Newcastle, UK. We have managed to establish ourselves as a trusted solution provider in the asset management industry.

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Edmonton International Airport invests in technology and innovation partners to create the next generation of convenience, efficiency, relaxation, and security for travelers. Overall passenger count grows by 4.2 percent (average) every year.


One critical infrastructure component that impacts passenger satisfaction and flight on-time departure performance is the baggage handling system. If baggage cannot be de-planed, sorted and transferred to connecting flights or moved to passenger collection points, gate operations and flights are delayed, and baggage is either late or misplaced. Modern handling systems comprise of an intricate set of scanners and conveyor belts located in the sub-levels of most airports. Failure of the drive motor or gearbox in any section of the system results in slow, manual and often error-prone movement of luggage. Failures during peak loads have a major impact on flight schedules and passenger satisfaction.


The 2018 Strategic Plan for the airport is customer-centric, focusing on increased efficiency. As a result, EIA was interested in solutions to reduce unplanned downtime on the baggage handling system. We proposed

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