OEE vs OOE vs TEEP: Which Manufacturing Metric Should You Track?
OEE, OOE, and TEEP all multiply Availability, Performance, and Quality, but they divide by different time bases. OEE uses planned production time, OOE uses all scheduled and unscheduled operating time, and TEEP uses every one of the 168 hours in a week. The metric you choose depends on whether you are fixing efficiency or judging capacity.
What is OEE and what time base does it use?
OEE (Overall Equipment Effectiveness) measures how effectively a machine performs during the time you planned to produce. It multiplies three factors: Availability (run time vs planned time), Performance (actual vs ideal cycle speed), and Quality (good parts vs total parts). Because the time base is planned production time only, OEE deliberately excludes breaks, planned maintenance, and unscheduled shifts, so it isolates the losses an operator or planner can actually fix.
OEE is the most actionable of the three. A low score points straight at downtime, slow cycles, or scrap. The widely cited world-class benchmark for OEE sits at 85%, though most shops find more value in tracking their own trend than chasing a single number. Continuous, machine-level OEE tracking turns this from a monthly spreadsheet guess into a live figure you can trust.
What is OOE and how does it differ from OEE?
OOE (Overall Operations Effectiveness) uses the identical Availability x Performance x Quality formula, but widens the time base to include all scheduled and unscheduled operating time. Where OEE asks "how well did we run during planned production?", OOE asks "how well did we run across everything we actually operated, including the unplanned hours we ended up using?"
The practical effect: OOE will usually read lower than OEE for the same machine, because it absorbs losses OEE sets aside. It is useful when unscheduled running is common and you want one honest figure that reflects real operations rather than the idealised plan.
What is TEEP and why does it matter for capacity?
TEEP (Total Effective Equipment Performance) extends the time base all the way to 168 hours per week — every calendar hour, whether you scheduled the machine or not. It is calculated as OEE multiplied by Utilization, where Utilization is planned production time divided by all 168 hours. TEEP therefore reveals total, theoretical capacity.
This makes TEEP the capacity lens. A machine can post a strong OEE during a single day shift yet have a low TEEP simply because it sits idle for two-thirds of the week. Before buying another machine, TEEP shows whether the headroom you are paying for already exists in nights and weekends.
How are OEE, OOE, and TEEP calculated side by side?
All three start from the same loss factors and differ only in the denominator. The table below shows the time base and the question each one answers.
| Metric | Formula | Time base | Best question to answer | |--------|---------|-----------|-------------------------| | OEE | Availability x Performance x Quality | Planned production time | How well do we run when we intend to run? | | OOE | Availability x Performance x Quality | All scheduled + unscheduled operating time | How well do we run across everything we actually operate? | | TEEP | OEE x Utilization | All 168 hours per week | How much total capacity is still untapped? |
The shared formula is the key insight: improving Availability, Performance, or Quality lifts all three metrics at once. The denominator only changes what story the final percentage tells.
Which metric should you track first?
Start with OEE. It points directly at the losses you can fix on the machines you already own — downtime, slow cycles, and scrap — and it is the metric operators understand most intuitively. OOE is a refinement for shops where unscheduled running is routine and you want a single, unflattering operational number. TEEP is a periodic capacity check, not a daily KPI.
A sensible sequence for a small-to-mid CNC shop is: run OEE continuously to drive daily improvement, glance at OOE when your schedule is volatile, and pull TEEP only when a capital or staffing decision is on the table. Tracking all three constantly tends to dilute focus rather than sharpen it.
How do you measure these metrics accurately on CNC machines?
Accurate metrics need accurate data, and that is where many programmes fail. Manual logs and surface-level signals miss micro-stops and misreport cycle states. xynLog reads native, controller-level data — not just MTConnect surface signals — directly from the control on Fanuc, Siemens, Heidenhain, Haas, Mazak, and similar machines, so Availability and Performance reflect what the spindle actually did.
That depth feeds real-time OEE tracking and machine monitoring, with condition-based alerts that flag developing issues from live signals rather than waiting for a breakdown. Native machine connectors handle the controller-level integration, and operators classify downtime reasons at the operator terminal so your Availability losses carry real causes, not guesses.
How does the AI assistant help you read these metrics?
Numbers only help if you can interpret them quickly. The built-in plain-language AI assistant lets a production manager ask, in normal words, "why did OEE drop on the Mazak last night?" or "which machine has the most untapped TEEP?" and get a grounded answer from your own live data. It runs on OpenAI or Claude, or fully on-premise with Ollama for shops that keep everything inside their own walls.
Because xynLog is EU-hosted (with on-prem options), your production data and metric history stay under your control, which matters for shops bound by data-residency requirements.
See xynLog on your own CNC brand — book a demo.
The bottom line
OEE, OOE, and TEEP are not competing scores; they are three lenses on the same loss factors. Use OEE to fix efficiency, OOE to see honest operational reality, and TEEP to judge capacity before you spend on more iron. Pick the lens that matches the decision in front of you — and make sure the data feeding it comes straight from the controller.