The data looks like it could lend itself to an approach where you model the error rate based on the prior data (at simplest, get a mean and variance out of it) and then use a Chi-square critical range check to see if the last n (degrees of freedom in the check) measurements are likely to have come out of the modelled distribution. Is that something you've considered?