You also get a new source of information with repeated measures. Now when you detect a failure it’s not just left censoring, but interval censoring: the failure happened somewhere between the previous observation and now.
However the machine may have already died in the previous observation, but due to the faulty sensor you didn’t know this. So it’s a mixture of all the possible censoring intervals, weighted by the sensor failure rate. You’ll probably need a custom likelihood for this.