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Last verified: 16 May 2026.<\/strong> Total Effective Equipment Performance (TEEP) is a manufacturing performance metric that measures actual production output against calendar time, rather than against planned production time as Overall Equipment Effectiveness (OEE) does. The metric was formalized by Robert C. Hansen in Overall Equipment Effectiveness: A Powerful Production\/Maintenance Tool for Increased Profits<\/em> (Industrial Press, 2001, ISBN 0-8311-3138-8) as an extension of Nakajima’s original OEE framework.<\/p>\n “TEEP measures OEE effectiveness against calendar hours, i.e., 24 hours per day, 365 days per year. TEEP, therefore, reports the ‘bottom line’ utilization of assets.”<\/em> \u2014 Robert C. Hansen, Overall Equipment Effectiveness<\/em>, Industrial Press, 2001, p. 28.<\/p>\n<\/blockquote>\n The distinction matters for capacity planning decisions. A plant manager asking “how well are my shifts running?” wants OEE. An executive asking “do I need to build a new factory?” wants TEEP. Confusing the two is the most common source of misallocated capital expenditure in manufacturing operations we observe across 450 factories in 30 countries.<\/p>\n TEEP is defined as:<\/p>\n TEEP = OEE \u00d7 Utilization<\/strong><\/p>\n where Utilization is the ratio of Planned Busy Time (PBT) to Calendar Time. Expanding:<\/p>\n TEEP = Availability \u00d7 Performance \u00d7 Quality \u00d7 Utilization<\/strong><\/p>\n Calendar Time is 24 hours per day, 7 days per week, 365 days per year. Utilization captures the gap between calendar time and the time the plant chose to schedule production. A plant running a single 8-hour shift, 5 days per week, has a Utilization ceiling of 23.8% (40 \u00f7 168). Even at 100% OEE during scheduled production, that plant’s TEEP cannot exceed 23.8%.<\/p>\n Consider an automotive Tier-1 stamping plant currently running two 8-hour shifts, Monday through Friday, with a measured OEE of 82% on the bottleneck press line. The Utilization is (80 hours \u00f7 168 hours) = 47.6%. The TEEP is 0.82 \u00d7 0.476 = 39.0%.<\/p>\n If the plant is at peak demand and considering a \u20ac40 million capacity expansion, the TEEP figure forces the prior question: of the 61% of calendar capacity currently unused, how much is recoverable through shift expansion versus genuinely unavailable? Adding a weekend shift could move Utilization to 71% with no capital expenditure; capturing that capacity recovers more output than the planned new line. Stellantis, a TeepTrak customer, identified \u20ac4.8 million in annual production losses through a comparable TEEP-versus-OEE decomposition exercise.<\/p>\n Hansen 2001 and Muchiri & Pintelon’s 2008 literature review in the International Journal of Production Research<\/em> (DOI: 10.1080\/00207540601142645) converge on a clear decision rule:<\/p>\n ISO 22400-2:2014 includes Utilization as a separately defined KPI in \u00a76 but does not name TEEP explicitly. The standard’s NEE (Net Equipment Effectiveness) is conceptually closer to TEEP in that it incorporates planned downtime, but the time baselines differ. For a strict ISO 22400 audit context, TEEP must be reported as the explicit product of OEE and the \u00a76 Utilization indicator, with the calendar baseline disclosed.<\/p>\n From the TeepTrak 450-factory dataset (anonymized aggregate, 2024 reporting year), median TEEP varies materially by sector and by shift-pattern norms:<\/p>\n Note that aerospace TEEP figures appear extremely low because the sector typically schedules a single shift on high-value capital equipment; the OEE component is comparable to other sectors, but the Utilization ceiling is much lower.<\/p>\n Three errors recur across deployments and corrupt TEEP-driven decisions:<\/p>\n OEE measures performance against Planned Busy Time; TEEP measures performance against Calendar Time. TEEP = OEE \u00d7 Utilization, where Utilization = Planned Busy Time \u00f7 Calendar Time.<\/p>\n No. Since Utilization is bounded between 0 and 1 (a plant cannot schedule more than calendar time), TEEP is always less than or equal to OEE.<\/p>\n There is no single world-class TEEP benchmark equivalent to Nakajima’s 85% OEE figure, because the achievable TEEP is bounded by the chosen shift pattern. For 24\/7 continuous operations the practical ceiling is approximately 75-80%; for single-shift operations the ceiling is approximately 22%.<\/p>\n ISO 22400-2:2014 \u00a76 defines Utilization as Actual Order Execution Time divided by Planned Order Execution Time at the order level, which differs from the TEEP usage where Utilization is Planned Busy Time over Calendar Time at the equipment level. For TEEP reporting, the calendar baseline must be disclosed.<\/p>\n The TEEP concept generalizes to any capital-intensive operation where calendar capacity matters. Hospital MRI machines, data centre servers, and aircraft fleets all benefit from TEEP analysis. The OEE component is adapted to the service context as documented in Garc\u00eda-Arca et al. (2018).<\/p>\n TEEP is a stricter measure than traditional capacity utilization because it incorporates the effectiveness of the time that is utilized. A line running at 100% capacity utilization but 60% OEE has only 60% TEEP under continuous operation.<\/p>\n Yes, alongside OEE. OEE tracks operational discipline; TEEP tracks asset productivity. Together they support both operational and capital decisions.<\/p>\n NEE, also defined in some interpretations of ISO 22400, accounts for planned downtime but uses Operating Time as the baseline rather than Calendar Time. NEE is conceptually between OEE and TEEP. Hansen 2001 treats NEE as transitional and recommends TEEP for capital-decision contexts.<\/p>\n Yes. TeepTrak measures TEEP at the same sampling frequency as OEE, with Utilization computed from the scheduling system rather than from sensor data. The calendar baseline is constant; the Planned Busy Time evolves as schedules are updated.<\/p>\n TEEP quantifies the unused calendar capacity within the existing asset base. Before committing capital to new equipment, TEEP analysis identifies whether the demand can be met by extending shift coverage, reducing planned downtime, or improving OEE on the bottleneck.<\/p>\n Author: Fran\u00e7ois Coulloudon, CEO, TeepTrak. Reviewed by Bastien Affeltranger, CTO. Cross-reference: OEE glossary entry<\/a>. Last verified 16 May 2026.<\/em><\/p>\n\n
The TEEP formula<\/h2>\n
Worked example: a Tier-1 plant evaluating capacity expansion<\/h2>\n
When to use TEEP versus OEE<\/h2>\n
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TEEP and ISO 22400<\/h2>\n
TEEP benchmarks by sector<\/h2>\n
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The most common TEEP misuses<\/h2>\n
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Frequently asked questions<\/h2>\n
What is the difference between TEEP and OEE?<\/h3>\n
Can TEEP exceed OEE?<\/h3>\n
What is the world-class TEEP benchmark?<\/h3>\n
How is Utilization defined under ISO 22400?<\/h3>\n
Is TEEP relevant for service operations?<\/h3>\n
What is the relationship between TEEP and capacity utilization?<\/h3>\n
Should TEEP appear on an executive dashboard?<\/h3>\n
How does TEEP relate to NEE (Net Equipment Effectiveness)?<\/h3>\n
Can TEEP be measured continuously?<\/h3>\n
How does TEEP support capacity expansion decisions?<\/h3>\n
References<\/h2>\n
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