OEE Benchmark by Industry 2026 — Find your positioning across 8 sectors
Most manufacturers don’t know how their OEE compares to peers. They benchmark against generic “world-class is 85%” claims that don’t fit their reality. Truth is: world-class OEE in pharma biologics is 78%, while in plastics extrusion it’s 87%. Sector context matters more than absolute numbers.
This industry OEE benchmark tool gives you median, top 25%, and world-class (top 10%) OEE rates across 8 manufacturing sectors and 30+ sub-industries. All data is calibrated on anonymized OEE measurements from 450+ TeepTrak deployments in 30 countries between 2018 and Q2 2026.
Enter your sector and current OEE — the tool tells you exactly which quartile you’re in, the OEE points needed to reach the next level, and where your gap likely sits (Availability, Performance, or Quality). No signup required.
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| Industry / Sub-industry | 🔴 Bottom 25% | 🟠 Median | 🟡 Top 25% | 🟢 World-class |
|---|---|---|---|---|
| Discrete manufacturing Automotive OEM |
52% | 64% | 76% | 86% |
| Food & Beverage Beverage & bottling |
50% | 62% | 74% | 85% |
| Pharmaceutical Tablets & solid forms |
45% | 58% | 72% | 84% |
| Cosmetics & personal care Skincare |
47% | 60% | 73% | 84% |
| Metals & metallurgy Steel & sheet metal |
50% | 63% | 76% | 86% |
| Plastics & rubber Injection molding |
50% | 63% | 76% | 86% |
| Aerospace & defense Engines & propulsion |
38% | 50% | 63% | 75% |
Methodology — How these benchmarks were calculated
Calibrated on real deployment data. All benchmark values come from anonymized OEE measurements collected across 450+ TeepTrak deployments in 30 countries between 2018 and Q2 2026. Each plant contributed minimum 90 days of validated OEE data with cross-line variance accounted for.
Quartile methodology. Bottom 25% = 25th percentile of plants in the sub-industry (75% perform better). Median = 50th percentile (typical performance). Top 25% = 75th percentile (data-driven plants). World-class = 90th percentile or higher (top 10% globally). All percentiles calculated on cleaned data with outliers (>3 standard deviations) removed.
Why benchmarks differ across sectors. Pharma biologics has lower theoretical max OEE (78% world-class) due to mandatory cleaning cycles and validation requirements. Plastics extrusion can sustain higher OEE (87%) due to continuous-flow nature. Always benchmark within your sector — cross-sector comparisons are meaningless.
Pillar breakdown. For each sector, we report median and world-class values for the three OEE pillars: Availability (uptime ratio), Performance (speed vs ideal), Quality (first-pass yield). Sectors typically have a "weakest pillar" pattern: pharma has highest quality benchmarks but lowest performance; plastics has highest performance but variable availability.
TeepTrak Industry OEE Benchmark Tool (Q2 2026), US edition. teeptrak.com/en/oee-benchmark-by-industry-2026/Updated quarterly. Benchmark values are refreshed every quarter as new deployment data accumulates. Last update: Q2 2026. Data freshness: 95% of values come from deployments in last 24 months.
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Frequently Asked Questions
What is the average OEE in manufacturing?
The average (median) OEE in manufacturing is around 60% across mid-market plants in 2026, but varies significantly by sector. Discrete manufacturing median: 60-67%. Food & beverage median: 55-62%. Pharma median: 50-63%. Plastics median: 60-66%. Aerospace median: 48-58% (lower due to complex products). World-class OEE (top 10%) ranges from 75% (aerospace composites) to 87% (plastics extrusion). Always benchmark within your specific sector — cross-sector comparisons are misleading.
What is world-class OEE?
World-class OEE represents the top 10% of manufacturers globally — typically 80-87% depending on sector. The often-quoted "85% is world-class" is sector-specific to discrete manufacturing. In reality: pharma biologics world-class is 78%, plastics extrusion world-class is 87%, food & beverage is 83-85%, automotive OEM is 86%. World-class plants share three traits: real-time OEE monitoring, predictive maintenance triggers, and OEE-aware operator culture.
What is a good OEE for my industry?
A "good" OEE depends on your sector. To assess: (1) Identify your sub-industry (e.g., automotive OEM vs Tier 1, dairy vs bakery). (2) Compare your OEE to median for your sub-sector — if above, you're in the top 50%. (3) Check the OEE points needed to reach top 25% — that's your near-term improvement target. (4) Top 10% (world-class) usually requires 18-24 months and a culture shift. Don't aim for "85%" if your sector's world-class is 78% — you'll burn out trying to hit an unreachable benchmark.
Why does OEE differ between food and pharma manufacturing?
OEE varies between sectors due to theoretical maximum constraints. Pharma manufacturing has lower achievable OEE (50-78%) due to mandatory clean-in-place cycles, validation requirements, and lot tracking that consume scheduled production time. Food manufacturing has higher achievable OEE (55-85%) but typically lower than plastics due to changeover frequency for SKU variety. Always benchmark within your sector — comparing pharma to plastics OEE numbers leads to wrong conclusions.
How were these OEE benchmarks calculated?
These benchmarks come from anonymized OEE measurements across 450+ TeepTrak deployments in 30 countries, collected between 2018 and Q2 2026. Each plant contributed minimum 90 days of validated data. Quartiles (bottom 25%, median, top 25%, top 10%) were calculated using percentile methodology with outliers (>3 standard deviations) removed. Data is updated quarterly. 95% of current values come from deployments in the last 24 months.
How long does it take to move from median to top 25% OEE?
Moving from median to top 25% OEE typically takes 6-12 months for mid-market plants. The first 3-5 OEE points are gained within 90 days through real-time tracking and operator dashboards. The next 3-5 points (months 3-9) come from structured Pareto analysis and targeted improvements on top causes. Reaching top 10% (world-class) requires 18-24 months and includes predictive maintenance triggers, AI anomaly detection, and a culture shift to data-driven operations. Realistic gain: +6-12 OEE points within 12 months.
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