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Streamlining troubleshooting in the field

Nieke Roos
Leestijd: 7 minuten

Canon Production Printing has teamed up with TNO’s joint innovation center ESI to identify potentially failing parts and predict potential issues in production printers. In the Carefree project, they’re developing hybrid AI technology to support service engineers.

“At Canon Production Printing, predictive maintenance has been a topic of interest for quite some time,” says Peter Kruizinga, a lead technologist at the Venlo-based company. “The aim is to get an accurate picture of when a printer or one of its components is going to break down by analyzing the machine’s data, and then dispatch a support engineer to preempt the issue. We’ve already successfully implemented this for the transport belts in our systems: a significant rise in power usage of a belt drive is a direct sign of impending failure, so when we see that happening, we can send someone over to replace the motor before it breaks down.”

Not all cases are so clear-cut, though. “A printer has thousands of parts,” notes Kruizinga. “For a lot of them, unfortunately, there are no such direct indicators, so in order to ascertain the source of a problem, we need a lot of indirect information, which often is unavailable. For a specific part, the failure mode can also vary from one situation to another. We realized that doing predictive maintenance on a structural basis requires us to solve a large number of puzzles, and to get all the pieces, we have to make strides in problem diagnosis.”

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