Does the algorithm continue to learn what is normal past the initial training period?
Yes, Asset Risk Predictor (ARP) uses the first 7 days as the initial training period, and then automatically retrains after one month. After that, it retrains every six months automatically.
Note
If you're using Fiix Prescriptive Maintenance, retraining might happen more frequently. To learn more, see How often does it retrain? in the Fiix Prescriptive Maintenance section.
How does the algorithm learn what is normal? Do we have to choose a “normal” week for implementation?
Ideally, we choose a week when the machine is behaving as we would like it to. However, we can retrain at any time if the machine does not run as expected during the training week.
What happens if something goes wrong with the asset during the training period?
Ideally the machine is sending out faults and ARP will disregard these sections of data and wait for clean data to train on. If this is not the case and machine fault information is not available, then we would trigger a relearn.
Does the algorithm account for degraded performance over the time we use ARP?
We’ve developed the retraining schedule for our algorithm with this in mind. By automatically retraining every six months, rather than on a more frequent schedule, we’re able to see degraded performance over time.