How do we do this?

The first step consists of a laser sensor that measures the height of the carrier in relation to the track. When the wheels wear off, the carrier will come closer to the track and lose height. This can cause the magnets on the carrier to come too close to the induction coil, which can lead to an emergency stop of the system to prevent collision damage. The emergency scenario is a practical example of unplanned downtime.  

The second step is placing four advanced cameras with their own backlighting surrounding the track. These cameras continually take images of the running- and guiding wheels of the carriers when passing by. The images are ingested in a data platform with an AI engine that applies corrections. By visually determining the wheel position on the track, the AI engine calculates the wheel dimensions with an accuracy of 0.15mm.

A great improvement on accuracy and coverage compared to previous manual caliper measurements which only covered about 10% of the carrier wheels, and left room for human error.

The third step consists of a vibration sensor placed on the track. This sensor detects vibrations caused by worn out bushes and/or bearings, and sends the data to the platform to be analyzed. Here, the vibration data is linked to a specific carrier by analyzing the vibration curve in the data in relation to the carrier’s position in time.

All of this data from the laser sensor, the cameras, and the vibration sensor is collected, processed, and combined into heatmaps on sorter, carrier, and component level. With that, the system determines the wear and tear on wheels.

It consequently suggests the site reliability engineers to intervene in time by quickly pinpointing components requiring maintenance. In addition, the maintenance planner can fully use and prioritize the upcoming maintenance windows or plan emergency repairs to prevent unplanned downtime.

• By developing this innovative solution, we enabled our customer to:
• Reduce planned downtime for manual inspection by 50%
• Increase the inspection percentage from 10% to 100%
• Increase accuracy and eliminate the risk of human error
• Reduce unplanned downtime
• Reduce the number of emergency stops
• Provide a more sustainable approach on spare parts utilization
• Gain valuable insights into the life cycle of their sorting systems.

So yes, the predictive maintenance techniques used in the “Carrier Health” system are actually reducing downtime.