You Have an OEE Number. Can You Explain It?
Many plants report an OEE figure that nobody fully trusts — availability that excludes undocumented downtime, performance measured against a theoretical rather than proven ideal cycle time, or a quality figure that misses rework. This audit reviews your actual definitions and data sources against a limited sample and tells you exactly where the number is solid and where it is not.
Audit our OEE data qualitySee all Proof of Concept programsWhat this checks
For a plant that already reports OEE but where the people who should act on it do not trust the inputs, or cannot explain what is driving a loss — the same trust gap the MES PoC guardrail already names, checked here before committing to a pilot.
What we do
- Review your current OEE metric definitions — availability, performance, quality — against how they are actually calculated today.
- Trace the data sources behind each: manual entry, PLC signal, MES record, spreadsheet formula.
- Check what is excluded from the calculation (planned stops, changeovers, startup scrap) and whether that exclusion is documented or assumed.
- Reconcile a limited sample of reported figures against an independent count, the same way every MSF PoC establishes its baseline.
What we need from you
- Your current OEE definitions and how each component (availability, performance, quality) is calculated.
- A sample of the underlying data for a defined period — stop logs, scrap records, cycle-time data — for one representative line.
- Your current stop/downtime classification codes, if you use them.
- Access to whoever currently compiles the OEE report, for a short walkthrough of the process.
What you get back
- An OEE data-quality score for the sample reviewed, with the evidence behind each component shown, not just a number.
- A list of what evidence is missing — undocumented exclusions, unclassified stop time, an ideal cycle time nobody has validated.
- The major distortion risks specific to your setup — the things most likely to be making the number look better or worse than reality.
- A recommended scope: an MES PoC for automated, defensible data capture, or an IIoT PoC where the gap is signal availability rather than definitions.
What this does not claim
This audit does not certify your OEE number as correct or incorrect — it identifies the evidence gaps behind it and how confident you can be in each component, on the sample reviewed. Full confidence requires the same reconciliation process an MES PoC runs continuously.
The Proof of Concept this leads to
Frequently asked questions
What if we do not have a formal OEE definition at all?
That is a common and useful starting point — the audit still works, using whatever calculation currently produces the number you report, and one output is a documented definition you can actually defend.
How much data do you need?
A limited, representative sample — typically one to two weeks on one line is enough to reconcile the components and identify where the evidence is thin, without asking for a large data export.
Does this replace the MES PoC?
No — it is the diagnostic step before it. The audit tells you specifically what an MES PoC would need to fix; the PoC itself installs the automated capture and proves the fix on your data.
Request this Proof of Concept
Tell us the scope you have in mind and we will come back with a written PoC plan: what gets connected, what you provide, how success is measured and what the decision at the end looks like.