PI System Data Resiliency · AF Governance
Every new project adds AF elements. Every site team builds their own template variations. Assets are renamed, templates are duplicated, analyses are left half-finished, and ownership becomes tribal knowledge. The result is an AF hierarchy that works at small scale but becomes fragile and unmanageable as it grows.
The same equipment type modeled differently across sites, making fleet-wide analytics impossible and governance effort multiply with every new site.
A template that works for two pumps may fail silently across thousands if the referenced tags are missing, renamed, or misconfigured at some sites but not others.
Analyses and templates that have accumulated complexity over years, with no documentation, no owner, and no safe way to understand the change impact before modifying them.
Tycho scans AF analyses for references to missing, stale, or invalid tags and surfaces exactly which analyses are silently failing across which assets. Teams stop discovering AF issues reactively through operator complaints and start managing them proactively.
Analyses pointing to tags that have been deleted, renamed, or moved, causing the analysis to fail or return incorrect results.
Analyses running on tags that are no longer receiving fresh data, silently propagating stale values through the AF hierarchy.
Analyses disabled for unknown reasons with no record of when, why, or what was affected. Invisible gaps in the asset model.
Multiple attributes representing the same measurement within or across templates, with no canonical version and no guidance on which one to use.
Template governance requires knowing how templates are actually used across the asset hierarchy — not just how they were designed. Tycho surfaces template variation, inheritance gaps, and elements that have drifted from their template definitions. This makes fleet-wide governance tractable instead of requiring manual inspection of every asset.
Understanding how an AF expression has changed over time is essential for root cause analysis and governance. Tycho shows expression history and enables before/after comparison so teams can trace calculation changes to their consequences in displays and reports.
See every version of a calculation expression: what it was, what it became, and when it changed. Essential context for root cause analysis when outputs drift unexpectedly.
For any expression change, understand what displays, reports, and downstream consumers relied on the previous calculation behavior.
Clean AF is the bridge from raw historian data to asset-aware analytics. When templates are consistent, analyses are reliable, and the hierarchy reflects reality, data scientists and analytics teams can build on PI data instead of spending their time cleaning and validating it.
Surface broken analyses, template inconsistencies, and calculation reliability gaps across your AF hierarchy before they block enterprise analytics or create operator-visible failures.
Tycho Data helps teams ensure their operational data is reliable, accessible, and actionable.