Off-The-Road (OTR) tyre failures pose a major safety and financial risk to mine operations.
In a worst-case failure, a tyre fire can occur, with the more likely outcome—if tyre damage is not identified— unplanned downtime for tyre changes plus the potential cost of $50,000 and potential injury to employees.
Not having any insight into active tyre damage on-site also makes forward planning of tyre stock difficult and can make change times longer.
To help its clients keep their highly valuable equipment and keep their workers safe, FLIR has provided key internal technology for the recently introduced Pitcrew AI system.
Pitcrew AI leverages FLIR’s state-of-the-art thermal imaging and AI technology to change the way trucking and mining vehicles are inspected.
The system utilises an AI algorithm trained on a library of thermal images, which allows the system to spot problems in their early stages, before equipment is destroyed or vehicles are involved in deadly accidents.
Built by Industrial Monitoring & Control (IMC), the automated system is designed specifically for the inspections of mining truck tyres.
This is critical to maintaining uptime for mining trucks, as even minor damage to a large mine tyre—such as a simple rock-cut—can result in complete tyre failure if not detected.
Pitcrew AI is able to detect small tyre injuries, such as rock drill, missing lug, or rock incisions. Each individual damage event can be tracked via an individual damage ID.
After the initial detection, the tyre can be inspected; and if it is repairable then the tyre can be removed and repaired, delivering savings on the site tyre spend.
Machine learning models are used to project the damage growth and predict when a tyre change is necessary. This allows vehicle downtime to be planned well in advance, minimising unplanned tyre changes and allows tyre stock to be managed efficiently.
Pitcrew AI system can detect hot tyres and immediately alert personnel via email, SMS or multiple other communication options.
When it came to automating inspections, IMC decided to use a FLIR A615 Thermal Machine Vision camera and trained an AI model to identify the early stages of separation as they appeared in thermal.
The Pitcrew AI system provides a user-friendly web dashboard, accessible from anywhere with an internet connection. The interface is optimised for mobile devices and users with poor network connections, as this is the most common method of access by our site users.
Detailed inspection history and automated reports are available. Insights into mine operations can be seen in the data and mine condition monitoring is possible.
Going Beyond Tyre Inspections
The underlying Pitcrew AI system was originally developed for roadgoing heavy vehicles, with a similar FLIR camera system already being used as a tool to automatically detect brake issues on cross-country trucks.
This system provides authorities with compliance information and fleet operators with predictive maintenance data.
SOURCE
TELEDYNE FLIR Systems
P 1300729987
E [email protected]
W www.flir.com.au/
