TEEP vs. OEE: The Equipment Effectiveness Metric You're Not Measuring

Every week, plant managers across North America review their OEE reports, see numbers in the 70–80% range, and conclude their equipment is running well. Many of them are right — during the hours those machines are scheduled to run. What the OEE report does not show is what the equipment was doing the other 16 hours of the day, or over the weekend, or during the two weeks of planned maintenance shutdown each quarter.

That is where TEEP — Total Effective Equipment Performance — enters the picture. TEEP is not a replacement for OEE. It is the upstream metric that puts OEE in context, and it is the number that changes capital investment conversations, shift scheduling decisions, and capacity expansion timelines.

After 35 years of working with manufacturers ranging from small job shops to Tier 1 defense suppliers, User Solutions has seen TEEP analysis prevent unnecessary machine purchases, justify second-shift expansions, and reveal hidden capacity worth millions in additional throughput — all without adding a single square foot of floor space.

What OEE Actually Measures (and What It Doesn't)

OEE is a well-established metric. The formula is:

OEE = Availability × Performance × Quality

• Availability = (Scheduled Time − Unplanned Downtime) / Scheduled Time
• Performance = (Ideal Cycle Time × Total Parts Produced) / Run Time
• Quality = Good Parts / Total Parts Produced

The critical word is "Scheduled." OEE only measures what happens during the time a machine is planned to be running. If you run one 8-hour shift Monday through Friday, OEE tells you how well the machine performed during those 2,000 hours per year. It says nothing about the other 6,760 hours.

World-class OEE is considered 85% or higher. Realistic targets for most discrete manufacturers are 65–75%. A machine running at 75% OEE during a single shift is performing well during its scheduled window — but that window may represent less than a quarter of all available calendar time.

The TEEP Formula: Adding the Loading Factor

TEEP adds one more variable: Loading, also called Utilization Rate.

Loading = Scheduled Production Time / Total Calendar Time

Total Calendar Time = 8,760 hours per year (24 hours × 365 days), or 744 hours per month.

TEEP = OEE × Loading

Or equivalently:

TEEP = Availability × Performance × Quality × Loading

A Concrete Example

Consider a horizontal machining center at a precision parts manufacturer:

• Scheduled hours: 8 hours/day × 250 working days = 2,000 hours/year
• Loading = 2,000 / 8,760 = 22.8%
• OEE = 76% (strong single-shift performance)
• TEEP = 76% × 22.8% = 17.3%

That machine is producing good parts at rated speed for just 17.3% of all calendar time. The remaining 82.7% of the year, it is either idle (planned downtime: off-shift, weekends, holidays) or losing performance (unplanned downtime, speed losses, quality defects).

TEEP Benchmarks by Industry

World-class TEEP = 85% or higher. This is achievable only in continuous-process industries running 24/7 with very high OEE — petrochemical plants, paper mills, some semiconductor fabs.

Realistic benchmarks for discrete manufacturers:

If your TEEP is below 30% on a claimed bottleneck machine, the bottleneck may be your schedule rather than the machine itself.

The Three Components of TEEP Losses

Understanding where TEEP losses occur is the key to prioritizing improvement investments.

1. Loading Losses (Planned Downtime)

Loading losses are the gap between calendar time and scheduled production time. They include:

• Off-shift hours (evenings, nights, weekends)
• Planned maintenance windows
• Changeover and setup time that falls outside production schedules
• Holidays and planned shutdowns
• Intentional underutilization (demand-driven idle time)

Loading losses are management decisions, not equipment failures. Raising Loading means adding shifts, moving maintenance to off-peak hours, or running weekends. These decisions require workforce planning, not maintenance work.

2. OEE Losses (Unplanned and Performance Gaps)

Within scheduled time, OEE captures three loss buckets:

• Availability losses: Unplanned breakdowns, changeover overruns, material starvation
• Performance losses: Speed reductions, minor stoppages, operator pace variability
• Quality losses: Scrap, rework, first-pass failures

These are the traditional domain of TPM (Total Productive Maintenance) and continuous improvement programs.

3. The Interaction Effect

OEE and Loading are multiplicative. A 10-point improvement in OEE (from 70% to 80%) on a single-shift machine raises TEEP by only 2.3 percentage points (from 16% to 18.3%). Adding a second shift (doubling Loading from 23% to 46%) raises TEEP by 16 points — even at the same OEE. This interaction explains why TEEP analysis so often leads to shift expansion decisions rather than equipment improvement projects.

How TEEP Drives Capital Investment Decisions

The most powerful use of TEEP is in capital planning conversations. The question "Should we buy another machine?" almost always has the same answer when viewed through the TEEP lens: not yet.

Here is the decision framework:

Step 1: Calculate current TEEP on the constrained machine. Step 2: Model the TEEP achievable by adding a shift or improving OEE. Step 3: Compare the incremental throughput from Step 2 against the capital cost of a new machine.

Example: The Second Shift vs. Second Machine Decision

A metal fabrication shop has a laser cutting center that is their bottleneck:

• Current: 1 shift, 8 hours/day, 250 days/year
• OEE: 72%
• Current output: 720 good parts/day (1,000 capacity × 72%)
• TEEP: 72% × 22.8% = 16.4%

Management wants to expand output by 50%. Options:

Option A — Add a second shift:

• Loading increases to 45.6% (2 shifts)
• TEEP rises to 32.8%
• Output: 1,440 good parts/day
• Cost: Workforce hiring, training, supervision — estimate $180K/year incremental labor

Option B — Buy a second laser cutter:

• Same output at same TEEP
• Cost: $350,000–$600,000 capital + installation + maintenance

TEEP analysis makes the choice obvious. Option A delivers the same throughput increase at roughly one-third the total 5-year cost. Without TEEP, the conversation stays at "we need more machine capacity." With TEEP, it becomes "we have machine capacity — we need schedule capacity."

TEEP, OEE, and the Relationship to Loading: The Full Picture

The three metrics work as a hierarchy:

TEEP = OEE × Loading
     = (Availability × Performance × Quality) × (Scheduled Time / Calendar Time)

When you report all three numbers together, you communicate:

• TEEP — overall asset utilization against theoretical maximum
• OEE — quality of execution during scheduled time
• Loading — how aggressively the asset is being scheduled

A plant with OEE = 82%, Loading = 45%, TEEP = 37% is executing well but underutilizing its equipment. The correct intervention is schedule expansion.

A plant with OEE = 58%, Loading = 85%, TEEP = 49% is over-scheduled and under-executing. The correct intervention is reliability improvement and OEE-focused TPM.

Both plants might show up as "adequate" in a KPI dashboard that only shows OEE. TEEP separates them and points to different solutions.

Practical Implementation: How to Start Tracking TEEP

If you are not currently collecting TEEP data, here is the minimal viable approach:

Step 1 — Define Calendar Time. Use 8,760 hours/year. This is fixed; do not adjust it.

Step 2 — Track Scheduled Production Time. This comes from your production schedule or RMDB schedule records. Every work order release and planned maintenance window contributes to this number.

Step 3 — Calculate Loading daily or weekly. Loading = Scheduled Hours / 168 hours (per week) or / 744 hours (per month).

Step 4 — Multiply by OEE. If you are already collecting OEE (or its components via machine monitoring), TEEP = OEE × Loading.

Step 5 — Review at the capital planning cadence. TEEP is most valuable at the monthly or quarterly operations review — the meeting where shift additions and equipment purchases are proposed.

The TEEP Report in EDGEBI

EDGEBI tracks both OEE and TEEP in real time, pulling schedule data from RMDB and production actuals from shop floor inputs. The dashboard displays:

• Rolling 30-day TEEP by machine center
• OEE component breakdown (Availability, Performance, Quality) within scheduled time
• Loading trend — are machines being scheduled more or less aggressively over time?
• TEEP vs. target — configurable per asset class

This integration matters because TEEP requires two data streams: schedule data (from planning) and performance data (from production). Systems that track only one stream can calculate OEE but not TEEP. Learn how OEE is calculated and benchmarked in our OEE guide.

Common TEEP Mistakes to Avoid

Mistake 1 — Treating TEEP as a performance score. A 20% TEEP is not necessarily bad. A single-shift job shop running to demand with 20% TEEP may be operating exactly right for its market. TEEP is a diagnostic tool, not a report card.

Mistake 2 — Applying TEEP to non-bottleneck machines. TEEP is most valuable on constrained resources — the machines that limit throughput. Applying it to machines with excess capacity creates noise.

Mistake 3 — Using TEEP to justify eliminating planned maintenance. Planned maintenance reduces Loading and therefore TEEP, but it is not a loss — it prevents unplanned downtime that destroys Availability. TEEP analysis should never be used to cut preventive maintenance.

Mistake 4 — Comparing TEEP across industries without context. A 40% TEEP in aerospace machining is excellent. A 40% TEEP in automotive stamping is a serious problem. Always compare within industry and asset class.

Connecting TEEP to the Broader KPI Framework

TEEP does not stand alone. It connects to several other operational KPIs that effective manufacturers track together:

• Schedule Adherence — If schedule adherence is low, Loading is being overstated (planned time is not actually being executed). TEEP will look better than reality.
• On-Time Delivery — High OTD with low TEEP suggests you have enough capacity but are not capturing the commercial opportunity. Low OTD with low TEEP suggests you need to improve OEE before adding more scheduled time.
• Throughput Rate — TEEP directly determines total throughput potential. Closing the gap between current TEEP and world-class TEEP quantifies the throughput ceiling you have not yet reached.

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Ready to track OEE and TEEP together on your shop floor? Contact User Solutions to see how EDGEBI surfaces both metrics in a single dashboard — pulling schedule data from RMDB and actuals from your production floor. Trusted by GE, Cummins, and BAE Systems for 35+ years, our tools help manufacturers make capital decisions based on real utilization data, not gut feel.