This is why we have developed a new module for Yanomaly: the Control Performance Degradation Detector (CPDD).
Unlike CLPM (Control Loop Performance Monitoring) or CPA (Control Performance Analytics) tools, Yanomaly will not necessarily raise an alert or report an issue if a loop performs worse than some theoretical concept of ideal control. Instead it uses AI to learn for each control loop what the normal performance is, then only alerts if a control loop becomes worse. This avoids unnecessary alerts on control loops that always had a bit of oscillation or sluggishness because that was found acceptable or the best compromise.
It is sufficient that the CPDD has access to the trend data of the setpoint and process variable. If it also has access to the controller output and controller mode, it can detect even more control issues faster.
Yanomaly does not interfere with the control. It only reads and analyses the data and reports the results.
Results: Customers report that on average 5 important control or sensor or actuator issues are found per month, for on average one alert per day, per group of 300 control loops that are monitored by Yanomaly's CPDD. Investigating an alert only takes a few minutes because the CPDD is specific about the type of issue that it has found, and with one click the user sees the relevant trend plots in the user-interface for further investigation.