Businesses that prioritize logistics invest heavily in conveyor systems to move and sort packages they ship. Conveyors are composed of many mechanical subcomponents such as bearings, belts, motors, and pulleys. When these subcomponents fail, they can damage the system, leading to downtime for the entire conveyor line, and result in late delivery of packages to customers. Amazon is looking to implement an autonomous maintenance identification unit to detect the failures of these components before they happen. Amazon attempted to create and implement such a unit, which they called the “Tote Ranger.” The original Tote Ranger was discontinued after about a year.
The original Tote Ranger did not save the Amazon’s RME team any time as they performed their daily preventative maintenance routine. As it made its way through the conveyor line, a maintenance technician had to walk the route with it because there was no other way to determine its location if a fault was detected. The unit was incapable of processing the data it collected and after its route, the technician had to download and manually interpret the data it collected. By improving upon the original Tote Ranger and making it capable of processing its own data, the technicians that formerly had to walk with the system will be able to save time looking for faults on the conveyor belts, and spend more time conducting necessary repairs as needed.
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