Streamlining troubleshooting in the field

“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.”