Update to better handle discrete data in Statistical Process Control

We understand that as well as continuous data arriving at high frequency, many processes also generate low frequency, or disrete data. An example might be a labs sample result, or perhaps a pyrometer reading taken on a plant walk-around.

It made sense then to make Widget Working View work better with this discrete data. This eliminates unnecessary flooding of alerts by detecting points of change in the trend and applying rules to just those points.

Instead of a huge range of alerts on discrete data only one or two points will be marked as breaking the rule, thereby cleaning up the data and making it easier to read.


Continuous Data


Discrete Data

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