What is TEEP? Calculation, Benchmarks & TEEP vs OEE (2026)

Total Effective Equipment Performance (TEEP) is a manufacturing KPI used to understand how much of an equipment investment is actually being utilized. While most manufacturers rely on Overall Equipment Effectiveness (OEE) to assess shop-floor performance, years of real-world use have revealed a critical blind spot: OEE only measures how well equipment runs when it is scheduled to run. It says nothing about the many hours assets sit idle due to planning decisions, demand patterns, labor availability, or maintenance strategy.

This gap matters. In many factories, equipment represents the largest capital investment on the balance sheet, yet significant capacity remains unused outside scheduled production hours. TEEP addresses this gap by extending measurement beyond scheduled production and into total calendar time—providing visibility into both operational performance and unused capacity.

To understand how TEEP does this, it’s important to be precise about what the metric actually measures.

What is TEEP?

TEEP measures the percentage of total calendar time that equipment spends producing good parts at the correct speed. Unlike OEE, which evaluates performance only during planned production, TEEP includes every hour of the day, whether production was scheduled or not. That means all 168 hours in a week and all 8,760 hours in a year are part of the calculation.

This distinction is fundamental. If a factory operates a single shift per day, OEE evaluates only those eight scheduled hours and ignores the remaining sixteen. TEEP counts them all. As a result, TEEP reveals how much of the equipment’s full potential is actually being used—not just how well it performs during active shifts.

TEEP Formula and Calculation

The math works the same way as OEE:

TEEP = Availability × Performance × Quality

But availability now means operating time divided by total calendar time, not just scheduled time. If a production line runs 120 hours per week at full speed with no defects, it has 71.4% TEEP (120 divided by 168). The other 48 hours might be maintenance time, unplanned downtime, or time when no production was scheduled.

Why TEEP Matters

TEEP matters because it connects operational performance to business value, not just shop-floor efficiency. While OEE shows how well equipment runs during scheduled shifts, it says nothing about how much of the asset you're actually using relative to what you paid for it. TEEP fills that gap.

For capital-intensive manufacturing, this difference is critical. Equipment often represents millions in investment, yet much of that capacity may sit idle due to scheduling choices, demand patterns, labor availability, or maintenance strategy. TEEP makes this visible. It answers the executive-level question: "Are we getting a return on our equipment, or is capacity hiding in plain sight?"

TEEP is especially valuable when:

• Customer demand is increasing and capacity feels tight
• Management is considering adding shifts or buying new equipment
• Capital expenditure decisions need justification
• Different plants or lines need to be compared at a high level

In many cases, TEEP reveals that the fastest and cheapest way to increase output is not buying new machines—but better utilizing the ones already installed. A modest TEEP improvement can unlock significant production capacity without additional capital investment.

Importantly, TEEP is not about pushing equipment to run 24/7 at all costs. Instead, it provides the data needed to make intentional, informed decisions about scheduling, staffing, maintenance, and growth.

TEEP vs OEE: Key Differences

OEE and TEEP both measure equipment performance, but they look at different things. The big difference is what time period they measure against.

Feature	OEE	TEEP
What it measures	How well equipment runs during scheduled time	How much of total time equipment actually produces
Time counted	Only planned production hours	Every hour (24/7, all year)
Who uses it	Production supervisors and operators	Executives and plant managers
Typical numbers	60-85% is good	30-80% depending on shifts
Main question answered	"How efficiently did we use our scheduled time?"	"How much are we actually using this equipment?"

Here's another simple example:

Your packaging line runs one 8-hour shift per day, Monday through Friday. In one week:

• You scheduled 40 hours of production
• Equipment actually ran well for 34 hours
• Your OEE: 85% - Great! The production team did an excellent job during their shift.
• Your TEEP: 20% - The equipment was productive for 34 out of 168 total hours in the week.

Both numbers are correct and useful. OEE shows your production team is doing their job well. TEEP shows the equipment sits unused most of the time. Whether that's okay depends on customer demand, labor costs, and your business strategy.

What Is a Good TEEP Score?

One of the most common questions manufacturers ask is: "What TEEP score should we target?" The answer depends entirely on your industry, shift strategy, and business model.

Industry-Specific TEEP Benchmarks:

• Continuous process industries (paper mills, chemical plants, refineries): 80-90% TEEP for critical equipment. These operations are designed for 24/7 production, and high TEEP reflects the economics of continuous processing.

• Two-shift batch manufacturers (automotive parts, packaging, electronics): 40-60% TEEP is typical. Even with excellent operational performance, running two 8-hour shifts five days per week caps theoretical maximum TEEP at 48%.

• Single-shift operations (job shops, specialized manufacturing): 25-35% TEEP is common and often optimal. Running one 8-hour shift per day limits maximum TEEP to about 24% even with perfect execution.

The key insight: good TEEP is relative, not absolute. A 35% TEEP might represent world-class performance for a single-shift custom manufacturer, while 65% TEEP could indicate serious underutilization for a continuous process line.

What matters most is:

1. Trend analysis: Is your TEEP improving or declining over time?
2. Internal benchmarking: How does similar equipment compare within your facility?
3. Business alignment: Does your TEEP support your capacity strategy and customer demand patterns?

Don't chase arbitrary TEEP targets. Instead, use TEEP to understand whether your equipment utilization matches your business strategy, identify capacity constraints before they become critical, and make informed decisions about shift additions or capital investments.

How to Use Both Metrics

Most companies track both OEE and TEEP. OEE stays the main tool for production supervisors and operators who focus on running equipment well during scheduled time. TEEP gives executives information they need for planning capacity, deciding on equipment purchases, and analyzing whether to expand into new markets.

To calculate TEEP correctly, you need to track time carefully. Many manufacturing systems already sort downtime into planned and unplanned categories for OEE. TEEP needs more detail:

• Scheduled production time: When equipment runs or could start running right away
• Planned maintenance: Regular maintenance windows
• Changeovers: Time spent switching between different products
• No orders: Equipment sits idle because not enough customers want products
• Operational limits: Problems with other equipment, not enough workers, or other constraints

Without clear categories, TEEP can unfairly punish good operational decisions. Equipment that creates bottlenecks should show high TEEP. Other equipment may correctly show lower numbers.

Real-World Examples

TEEP works best in industries where equipment can run around the clock. Paper mills, chemical plants, and steel factories typically target higher TEEP values for their main production equipment since continuous operation makes business sense for these processes.

Industries that make distinct products in batches usually see lower numbers. This makes sense when you think about it: a factory running two eight-hour shifts, five days per week, can only reach about 48% TEEP even if everything runs perfectly during those scheduled hours.

The automotive industry shows why context matters. Assembly lines often run two shifts per day. Even with excellent operational performance during scheduled production time, TEEP numbers naturally stay lower. This reflects intentional business decisions about shift schedules, labor costs, and maintenance planning rather than poor performance.

Common Mistakes to Avoid

Several problems come up when companies use TEEP incorrectly. One major mistake is using TEEP to judge daily operations. Production workers cannot control customer demand or high-level scheduling decisions. Holding supervisors responsible for TEEP creates bad incentives to build unnecessary inventory or skip planned maintenance.

Another common error is ignoring the bigger picture. Equipment designed to handle product changes, quality testing, or work with other equipment should not be compared to equipment that runs continuously. A 35% TEEP might be the best possible number for a packaging line that serves multiple production lines.

Finally, many companies make the mistake of treating TEEP as a fixed target. TEEP helps you compare performance over time or across similar equipment. A dropping TEEP trend means you should investigate. But any single TEEP number needs context to understand what it means.

Using TEEP for Capacity Planning

TEEP helps most when planning capacity. When customer demand gets close to what you can produce, companies face a big decision: spend money to expand capacity or accept slower growth. TEEP analysis clarifies this choice by showing how much extra capacity exists in current equipment.

A factory with 65% TEEP across major equipment could theoretically increase production by 54% without buying new equipment, assuming customer demand exists and operational problems can be solved. Whether this capacity can actually be used depends on shift schedules, worker availability, maintenance needs, and product mix—but TEEP shows the theoretical maximum.

Setting Up TEEP Measurement

Companies that want accurate TEEP need good data collection systems. Writing down times by hand produces unreliable results. Automated data capture from equipment computers, control systems, or manufacturing software provides the foundation for accurate calculations.

The money spent on measurement systems should match decision-making needs. Companies making frequent capacity investment decisions benefit from real-time TEEP monitoring. Organizations with stable capacity and clear bottlenecks might find quarterly manual calculations work fine.

Building TEEP dashboards has become much simpler with modern tools. FlowFuse offers a practical solution for companies that want real-time equipment monitoring without complex programming. The platform bridges the gap between OT (Operational Technology) on the factory floor and IT systems in the office. It connects directly to your equipment—whether through PLCs, SCADA systems, or machine controllers and MES platforms—and creates visual dashboards that track performance metrics. You can see how straightforward the process is by looking at their OEE dashboard blueprint. The same approach works for TEEP—connect your data sources, set up the calculations, and view your equipment utilization in real-time. This makes professional-grade monitoring accessible even for smaller manufacturers or companies without dedicated programming staff.

Want to see how TEEP monitoring would work for your specific equipment and production environment? Book a demo with FlowFuse to explore how you can track equipment utilization, identify capacity opportunities, and make data-driven decisions about your manufacturing assets.

The Bottom Line

TEEP extends equipment measurement from operational efficiency to overall asset use. It does not replace OEE but adds to it by answering questions OEE cannot answer. When used carefully with proper context, TEEP gives manufacturing leaders clear visibility into total equipment productivity. It helps inform capacity investment decisions with solid numbers. The value is not in achieving high percentages but in understanding what those percentages reveal about equipment use, customer demand, and operational constraints.