Earlier quoted context omitted.
I think some sort of anomaly detection would be useful in your case. There are a bunch of libraries floating about, I remember at least Netflix[1], Yelp and Datadog talking about them. There appears to be a really good links page available too[1]. You can also learn a lot from Forecasting Principles and Practice , which is free online[2] I have previously pitched using a kind of SPC-for-metrics approach, with Nelson…
thanks for the links. We only create an alert if there is a problem the operator can solve, otherwise there is no point in waking them up at 3 AM, so if anything our thresholds are set as loose as possible instead of as tight as possible. However there are many instances where the operator could be alerted earlier that the machine operation is abnormal. For example the stator windings are rated for operation up to 15…
One thing I've wondered in the past year is whether fuzzy logic would be useful. Your example is a really good case of linguistic variables -- "lightly loaded", "a long time", "normal temperature" and so on. These can be assembled into rules or tables that should fire more sensibly than exact threshold values.