Outcomes, by function.
Gauge.ID returns canonical identities, duplicate findings, and a signed replayable report. Engineering, quality, and procurement each stop paying for something different.
Know whether the part already exists before anyone models it again. A canonical identity per part — invariant to translation, rotation, and reflection — makes the library searchable by geometry instead of by file name. Reuse becomes the default; redesign becomes a decision.
Every finding is recorded with the policy it was judged under, in a signed report you can replay — same inputs, same policy, byte-identical results. Parts that cannot be certified are flagged for engineering review, never silently guessed. That is an evidence trail you can hand to an auditor.
Duplicate and near-duplicate findings arrive as consolidation candidates keyed to part numbers: fewer parts to source, stock, inspect, and carry. Size the exposure with your own numbers — the worksheet below — before anyone commits to a cleanup.
Four inputs you can estimate today, plus one declared assumption. The worksheet computes annual exposure from part duplication. Defaults are industry planning estimatesA — every value is editable, and the results update as you move a control.
| Line | Value / yr |
|---|---|
| Duplicate findings actioned | 1,125 |
| Engineering hours recovered | 4,500 |
| Modeled annual avoided cost | $382,500 |
avoided cost = files × duplicate rate × capture factor × hours per duplicate × hourly cost
Assumes 75% of duplicate findings are actioned before rework begins Modeled. Outputs are planning estimates computed from your inputs — not measurements of your library.
- A Default input values are industry planning estimates (duplicate-rate and per-part cost ranges published in PLM industry studies), not Gauge.ID measurements. Every input is editable; the output is a model of your inputs, nothing more.
- B The 75% capture factor is a modeled assumption about how many findings are actioned before rework begins. It is declared, visible, and adjustable above.
Requirements, change orders, design reviews, audit files — your compliance stack runs on citable identities. Documents have them; drawings have them; the geometry itself never has. A Gauge.ID gives every part an identity your records can cite and your auditors can re-verify.
A requirement is verified against geometry — but the traceability matrix cites a filename that can drift. Cite the Gauge.ID instead: a requirement attribute naming the exact geometry it was verified against, checkable years later by re-running the report. It is plain text; it pastes into any requirements tool you run today.
Did this change order actually change the part? Before-and-after Gauge.IDs answer it under your declared policy: same identity — no geometric change; different identity — a change your board can see, record, and sign off. The replayable record attaches to the change package as evidence.
A design output entered in the DHF or first-article package carries a content-derived identity: the file you archived is provably the file that was reviewed and approved. An auditor does not have to take your word for it — they re-run the check.
A baseline that lists Gauge.IDs is a baseline of geometry, not of filenames. Renames, migrations, and format conversions stop silently corrupting configuration status accounting — and the part set your CDR approved stays enumerable, part by part, for the life of the program.
Citations are plain text and signed records attach to whatever tools you already run — usable today, no connector required. Native requirements and PLM connectors (ReqIF, Teamcenter, Windchill) are roadmap items Target.
Put numbers on it, then verify them.
The worksheet models the exposure; a pilot audit measures your actual library. A sample of your parts, a declared policy, a signed replayable report.