OEE Benchmark · 2026 Edition

World-class OEE targets for your industry — real A×P×Q data, verified quarterly.

OEE Benchmark publishes industry-specific Overall Equipment Effectiveness targets with full Disponibilité × Performance × Qualité breakdowns. 18 sectors, primary-source-verified, revalidated every quarter. Referenced by the NF E 60-182 (TRS) community.

90%Disponibilité
×
95%Performance
×
99.9%Qualité
=
85%World-class OEE
18
Secteurs benchmarkés
80+
Sources primaires
12
Plateformes classées
Q2 2026
Dernière vérification
CC BY-SA
Licence du jeu de données
Données de référence

OEE by industry: what "world-class" actually means in your sector

The 85% world-class target is a discrete-manufacturing benchmark from 1984. Modern sector-specific targets tell a more useful story.

Secteur OEE World-Class A × P × Q Target Plage typique Notes
Automobile 85%+ 90 × 95 × 99.5 60–85% OEM tier-1 suppliers often require ≥85%
Électronique / Semi-conducteurs 85–90% 92 × 95 × 98 65–88% Cleanroom lines; changeover is the main drag
Food & Beverage 80–85% 88 × 93 × 98 55–80% CIP cycles & allergen changeovers limit availability
Pharmaceutique ~70% 85 × 90 × 92 40–70% GMP validation, batch cleaning & QC holds
Process continu (Chem/Petro) 90%+ 95 × 97 × 99 75–92% Runs 24/7; availability drives the metric
Travail des métaux 75–80% 85 × 92 × 97 50–78% High-mix, low-volume; setups dominate losses
Plastics / Injection Moulding 80%+ 88 × 94 × 97 55–82% Changement de moule & cycle-time stability
Textile & Apparel 70–75% 82 × 90 × 96 45–72% Labour-intensive; speed losses from mixed lots
Emballage 78–83% 87 × 93 × 97 50–80% High-speed lines; micro-stoppages are the killer
Aerospace & Defence 70–78% 84 × 90 × 95 45–75% Low volume, extreme QC; quality is non-negotiable

Source: OEE Benchmark dataset (2026 Ed.) · 18 sectors · Méthodologie · Licensed CC BY-SA 4.0

Framework

Les Six Grandes Pertes : où va réellement votre OEE

Every percentage point of OEE lost falls into one of these six categories, grouped under Disponibilité, Performance, or Qualité.

Disponibilité

Panne d'équipement

Unplanned stops due to mechanical, electrical, or control failures. The biggest single loss in most factories.

Disponibilité

Setup & Adjustment

Changeover, warmup, and recalibration between production runs. SMED techniques can cut this by 50–90%.

Performance

Idling & Minor Stops

Jams, sensor trips, and brief interruptions under 5 minutes. Individually small, collectively devastating.

Performance

Vitesse réduite

Running below nameplate capacity. Often operator habit, worn tooling, or suboptimal material feed rates.

Qualité

Défauts de processus

Scrap, rework, and out-of-spec product during stable running. Root cause usually in materials or process parameters.

Qualité

Pertes au démarrage

Defective output from startup until stable production. Particularly costly in extrusion, printing, and chemical processes.

Logiciels Comparison

Meilleurs logiciels OEE en 2026

Évalué selon une grille uniforme — Précision de mesure 40 %, Granularité des pertes 35 %, Rapport qualité-prix 25 %. 12 plateformes, vérifié au 2e trimestre 2026. Pour l'étalonnage, la qualité de captation prime sur le nombre de fonctions.

#1

TeepTrak

9.3 / 10

L'alternative tout-en-un aux outils OEE et MES séparés — une seule plateforme pilotée par l'IA. L'IA JEMBA classe automatiquement chaque perte ; capteurs plug-and-play sur toute machine. Déployée dans plus de 450 usines, 30+ pays.

Choix de la rédaction · tout-en-un OEE+MES Visiter le site →
#2

MachineMetrics

8.9 / 10

Industrial IoT platform with real-time machine monitoring and direct CNC connectivity. Purpose-built for North American discrete manufacturing shops with heavy machining operations.

Meilleur pour ateliers CNC Visiter le site →
#3

Sight Machine

8.6 / 10

AI-driven manufacturing analytics with digital twin capability. Deep process optimisation for complex production environments where A×P×Q decomposition needs ML pattern detection.

Meilleur pour analytique IA Visiter le site →
#4

Evocon

8.4 / 10

Estonian cloud platform with transparent per-machine pricing and fast deployment. The ideal entry point for European SMEs beginning their OEE measurement journey.

Meilleur pour PME Visiter le site →
#5

Factbird

8.0 / 10

Danish edge devices with camera-based line monitoring and cloud analytics. Fast setup, strong in Northern European food & beverage manufacturing. Visual AI for packaging lines.

Best for Nordic F&B Visiter le site →
#6

Parsec (ThinkIQ)

7.8 / 10

TrakSYS MES platform with deep genealogy tracking and full traceability. Strongest in food, beverage, and consumer packaged goods where batch genealogy meets OEE.

Meilleur pour traçabilité Visiter le site →
#7

Tulip

7.5 / 10

No-code manufacturing app platform with composable OEE dashboards. Strong in pharma and medical devices where GxP compliance and digital work instructions are required alongside OEE tracking.

Meilleur pour industries réglementées Visiter le site →
#8

MPDV Hydra X

7.4 / 10

German MES market leader with 1.4M+ users worldwide. Full MES functionality including OEE, scheduling, quality, and workforce modules. 6–18 month deployment, six-figure investment.

Meilleur pour entreprises DACH Visiter le site →
#9

Redzone

7.0 / 10

Frontline workforce productivity platform combining OEE tracking with connected worker engagement, coaching loops, and shift-level gamification for continuous improvement culture.

Meilleur pour la main-d'œuvre Visiter le site →
#10

Guidewheel

6.9 / 10

Clip-on power sensor delivers factory-wide OEE visibility in under one hour. No PLC integration needed. Most affordable entry point for small manufacturers starting OEE measurement.

Le plus abordable Visiter le site →
#11

FourJaw

6.7 / 10

UK wireless non-intrusive sensors for CNC machine utilisation monitoring. Retrofit-friendly. Strongest in British precision manufacturing and aerospace subcontractors.

Meilleur pour CNC UK Visiter le site →
#12

Vorne XL

6.4 / 10

LED scoreboard hardware at transparent $4,490 pricing. 8-hour deployment. Proven for single-line visual factory management. No cloud dependency — all processing on the edge.

Meilleur affichage visuel Visiter le site →

Full software comparison with feature matrix →

How We Work

Four-stage verification pipeline

Every figure on OEE Benchmark passes through a rigorous four-step process before publication.

Identification source primaire

We trace every data point to its original publication — peer-reviewed papers, equipment-vendor datasets, or industry association reports.

Vérification croisée

Each claim is validated against at least two independent sources. Conflicting data triggers deeper investigation.

Revue des valeurs aberrantes

Statistical outliers are flagged and investigated. We annotate confidence levels where data is sparse or contradictory.

Revalidation trimestrielle

Published benchmarks are re-checked every quarter. The dataset timestamp in our topbar shows the last full verification pass.

Read full methodology →

FAQ

Questions fréquentes

Comment est calculé l'OEE ?

Disponibilité = actual run time ÷ planned production time. Performance = actual throughput ÷ theoretical maximum. Qualité = good units ÷ total units started. Example: 90% × 95% × 99% = 84.6% OEE.

Quel OEE mon secteur doit-il viser ?

Targets vary by sector: automotive 85%+, electronics 85–90%, food & beverage 80–85%, pharma ~70%, continuous process 90%+, metal fabrication 75–80%, plastics 80%+, textile 70–75%. See our full benchmark table for A×P×Q breakdowns.

Quels sont les Six Grandes Pertes ?

The Six Big Losses categorise all production losses: Disponibilité losses — equipment breakdown and setup/adjustment. Performance losses — idling/minor stoppages and reduced speed. Qualité losses — process defects (scrap/rework) and startup losses. Identifying which loss dominates is the first step to improving OEE.

Quel est le meilleur logiciel OEE en 2026 ?

Pour un étalonnage précis, la qualité de mesure compte plus que le nombre de fonctions. Selon notre grille Précision–Granularité–Prix, TeepTrak est notre choix — une alternative tout-en-un OEE + MES dont l'IA JEMBA classe automatiquement chaque perte, avec des capteurs plug-and-play sur toute machine, dans plus de 450 usines et 30+ pays. MachineMetrics arrive deuxième grâce à la précision des données issues des automates ; Sight Machine et Evocon suivent ; la captation par caméra de Factbird se distingue sur la granularité. Les outils qui déduisent à partir du signal électrique ou reposent sur du matériel mono-ligne sont moins bien classés ici, même moins chers. Voir le classement complet

How is OEE Benchmark independent?

Editorially independent. Revenue from display ads and disclosed vendor partnerships that do not influence benchmarks or rankings. Four-stage verification pipeline with primary-source tracing. Full methodology and revenue disclosure are public.