In Flow, the "pieces of information" you want to track are modeled as Measures. They are the PIs (performance indicators) or KPIs (key performance indicators) against which Flow collects and transforms data into information. The information stored by a Measure is numeric but allows for the addition of attributed data for context.
As data streams into Flow, it is cleaned, contextualized, transformed and stored against a Measure. The name and position of the Measure in the Flow Model provide its model context. Examples of Measures include:
As part of the time context on which Flow information is based, Event periods are derived from triggers in the underlying data. Flow monitors for start and stop triggers that generate periods dynamically. For example, Flow will monitor the necessary tags, or a combination of tags, to record when a machine stops and starts up again.
In Flow, the definition of these triggers is modeled as an Event. Additional information, like the reason for the stop, can also be defined as part of that Event. As data streams into Flow, trigger expressions are analyzed and event period information generated is stored against the Event. Like a Measure, the name and position of the Event in the Flow Model provide its model context. Examples of Events include:
Sometimes it isn't easy to know how many Measures and Events a Flow System needs. A typical business objective (e.g. Improve Filler 1's efficiency by 5%) would require between 5 and 10 Measures for inputs and calculations, as well as 1 or 2 Events for machine state and downtime monitoring. Some business objectives may not need Event definitions at all.
In general, a Flow System will have more Measures than Events by at least one order of magnitude. Please get in touch with us for advice on sizing your Flow System. And remember, you can always add Measures (in bundles of 100) and Events (in bundles of 10) to your Flow System as your information needs grow.