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A tag name is not an asset. PLANT2.U3.BRG.VIB.01 means something to the engineer who configured it in 2011 and nothing to anyone else — not to a new hire, not to a reporting tool, and not to a machine-learning model. The AVEVA PI Asset Framework is where that institutional knowledge becomes structure the whole organisation can use.
Most PI estates have an AF model. Far fewer have one that is complete, consistently templated, and trusted enough to build on. LAMR designs and rebuilds AF models so they describe the plant as it exists today and keep describing it as the plant changes.
Every downstream capability inherits the quality of the AF model. Dashboards built on an inconsistent hierarchy need rebuilding per site. Analytics trained on unmapped tags learn the quirks of one unit and fail on the next. Cloud and lakehouse programmes that lift tags without carrying context produce an expensive archive rather than a data product — the single most common and most costly mistake we are asked to correct.
Done properly, an engineer can ask for bearing vibration across every Unit 3 class asset without knowing a single tag name, and the answer means the same thing at every site.
We start from the plant and the people who run it, not from the existing tag list. Where an AF model already exists we assess it first and rebuild only what needs rebuilding. Templates, naming standards and documentation are handed over so your own team can extend the model without calling us — the measure of a good engagement is that it ends.