{"id":92593,"date":"2026-05-06T12:31:17","date_gmt":"2026-05-06T12:31:17","guid":{"rendered":"https:\/\/teeptrak.com\/methodologie-benchmark-trs-2026\/"},"modified":"2026-05-06T12:31:17","modified_gmt":"2026-05-06T12:31:17","slug":"methodologie-benchmark-trs-2026","status":"publish","type":"post","link":"https:\/\/teeptrak.com\/en\/methodologie-benchmark-trs-2026\/","title":{"rendered":"Benchmark TRS 2026 \u2014 M\u00e9thodologie"},"content":{"rendered":"<p><script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"Article\",\n  \"headline\": \"Benchmark TRS 2026 \u2014 M\u00e9thodologie\",\n  \"alternativeHeadline\": \"Comment le dataset 450+ usines a \u00e9t\u00e9 construit, valid\u00e9 et analys\u00e9\",\n  \"datePublished\": \"2026-05-06T08:00:00+02:00\",\n  \"dateModified\": \"2026-05-06T08:00:00+02:00\",\n  \"author\": {\n    \"@type\": \"Organization\",\n    \"name\": \"TeepTrak Manufacturing Research\",\n    \"url\": \"https:\/\/teeptrak.com\/fr\/a-propos\/\"\n  },\n  \"publisher\": {\n    \"@type\": \"Organization\",\n    \"name\": \"TeepTrak\",\n    \"url\": \"https:\/\/teeptrak.com\",\n    \"logo\": {\n      \"@type\": \"ImageObject\",\n      \"url\": \"https:\/\/teeptrak.com\/wp-content\/uploads\/teeptrak-logo.png\"\n    }\n  },\n  \"mainEntityOfPage\": {\n    \"@type\": \"WebPage\",\n    \"@id\": \"https:\/\/teeptrak.com\/fr\/methodologie-benchmark-trs-2026\/\"\n  },\n  \"description\": \"M\u00e9thodologie compl\u00e8te du Benchmark TRS TeepTrak 2026 : 450+ usines, 30 pays, secteurs ISIC R\u00e9v. 4. Donn\u00e9es direct-capteur, calibration P10, validation.\",\n  \"isAccessibleForFree\": true,\n  \"license\": \"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\",\n  \"inLanguage\": \"fr-FR\",\n  \"isPartOf\": {\n    \"@type\": \"Dataset\",\n    \"name\": \"Benchmark TRS 2026\",\n    \"url\": \"https:\/\/teeptrak.com\/fr\/benchmark-trs-2026\/\"\n  }\n}\n<\/script><\/p>\n<p><script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"Dataset\",\n  \"name\": \"Benchmark TRS 2026 \u2014 Dataset source\",\n  \"description\": \"Donn\u00e9es TRS direct-capteur de 453 usines industrielles dans 30 pays, janvier 2018 \u00e0 juin 2026. Anonymis\u00e9 au niveau usine ; secteur et pays pr\u00e9serv\u00e9s.\",\n  \"url\": \"https:\/\/teeptrak.com\/fr\/benchmark-trs-2026\/\",\n  \"license\": \"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\",\n  \"creator\": {\n    \"@type\": \"Organization\",\n    \"name\": \"TeepTrak Manufacturing Research\"\n  },\n  \"temporalCoverage\": \"2018-01-01\/2026-06-30\",\n  \"spatialCoverage\": \"Mondial (30+ pays)\",\n  \"variableMeasured\": [\n    \"Taux de Rendement Synth\u00e9tique (TRS)\",\n    \"Disponibilit\u00e9\",\n    \"Performance\",\n    \"Qualit\u00e9\",\n    \"Arr\u00eats par cat\u00e9gorie\",\n    \"Temps de cycle\"\n  ],\n  \"measurementTechnique\": [\n    \"Capteurs amp\u00e8rem\u00e9triques sur variateurs moteurs\",\n    \"Capteurs photo\u00e9lectriques aux sorties pi\u00e8ces\",\n    \"Int\u00e9gration automate (30+ marques de contr\u00f4leurs)\"\n  ],\n  \"includedInDataCatalog\": {\n    \"@type\": \"DataCatalog\",\n    \"name\": \"TeepTrak Manufacturing Research\"\n  }\n}\n<\/script><\/p>\n<p>[et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.27&#8243;][et_pb_row][et_pb_column type=&#8221;4_4&#8243;][et_pb_text]<\/p>\n<h1>Benchmark TRS 2026 \u2014 M\u00e9thodologie<\/h1>\n<p style=\"font-size:18px;color:#666;margin:0 0 32px 0;\">Comment le dataset 450+ usines a \u00e9t\u00e9 construit, valid\u00e9 et analys\u00e9.<\/p>\n<div style=\"display:flex;gap:24px;flex-wrap:wrap;padding:16px;background:#FAF8F5;border-radius:4px;margin-bottom:32px;font-size:14px;\">\n<div><strong style=\"color:#EB352C;\">Publi\u00e9 :<\/strong> Mai 2026<\/div>\n<div><strong style=\"color:#EB352C;\">Derni\u00e8re revue :<\/strong> Mai 2026<\/div>\n<div><strong style=\"color:#EB352C;\">Licence :<\/strong> CC BY 4.0<\/div>\n<div><strong style=\"color:#EB352C;\">Auteur :<\/strong> TeepTrak Manufacturing Research<\/div>\n<\/div>\n<div style=\"background:#FAF8F5;border-left:4px solid #EB352C;padding:20px;margin:20px 0;\">\n<p style=\"margin:0 0 8px 0;\"><strong>R\u00e9sum\u00e9<\/strong><\/p>\n<p style=\"margin:0;\">Le Benchmark TRS 2026 agr\u00e8ge des donn\u00e9es de production direct-capteur issues de 453 usines industrielles \u00e0 travers plus de 30 pays, entre janvier 2018 et juin 2026. Toutes les valeurs sont calcul\u00e9es \u00e0 partir de donn\u00e9es brutes machine et cycle. Aucune valeur de TRS auto-d\u00e9clar\u00e9e n&#8217;est incluse. Les segmentations sectorielles utilisent la classification ISIC R\u00e9v. 4. Le dataset est anonymis\u00e9 au niveau usine ; secteur et pays sont pr\u00e9serv\u00e9s. Cette page documente la collecte de donn\u00e9es, les r\u00e8gles de calcul, les \u00e9tapes de validation, les m\u00e9thodes statistiques et les limitations connues.<\/p>\n<\/div>\n<h2>1. Sources de donn\u00e9es<\/h2>\n<h3>1.1 Donn\u00e9es direct-capteur uniquement<\/h3>\n<p>Le benchmark utilise des donn\u00e9es de production capt\u00e9es directement depuis la plateforme de monitoring TeepTrak chez les clients d\u00e9ploy\u00e9s. Trois types de capteurs alimentent le dataset :<\/p>\n<ul>\n<li><strong>Pinces amp\u00e8rem\u00e9triques<\/strong> sur variateurs moteurs \u2014 d\u00e9tectent l&#8217;\u00e9tat machine (en marche\/\u00e0 l&#8217;arr\u00eat) \u00e0 granularit\u00e9 sub-seconde<\/li>\n<li><strong>Capteurs photo\u00e9lectriques<\/strong> aux sorties pi\u00e8ces \u2014 comptent les unit\u00e9s produites en temps r\u00e9el<\/li>\n<li><strong>Int\u00e9gration automate<\/strong> avec plus de 30 marques de contr\u00f4leurs (Siemens, Rockwell, Mitsubishi, Omron, Schneider, Beckhoff, ABB, Fanuc, et autres) lorsque des interfaces num\u00e9riques sont disponibles<\/li>\n<\/ul>\n<p><strong>Aucune valeur de TRS auto-d\u00e9clar\u00e9e n&#8217;est incluse dans le benchmark.<\/strong> C&#8217;est le choix m\u00e9thodologique le plus important. La plupart des chiffres TRS publi\u00e9s dans l&#8217;industrie reposent sur des relev\u00e9s op\u00e9rateurs ou des synth\u00e8ses de fin d&#8217;\u00e9quipe, que le dataset du benchmark lui-m\u00eame montre peu fiables. La mesure direct-capteur r\u00e9v\u00e8le des valeurs de TRS inf\u00e9rieures de 13,4 points de pourcentage en moyenne par rapport au TRS auto-d\u00e9clar\u00e9 \u2014 voir Section 4.<\/p>\n<h3>1.2 Crit\u00e8res d&#8217;inclusion des usines<\/h3>\n<p>Pour \u00eatre incluse dans le benchmark, une usine doit remplir tous les crit\u00e8res suivants :<\/p>\n<ul>\n<li>Minimum 90 jours cons\u00e9cutifs de capture de donn\u00e9es continue<\/li>\n<li>Au moins 3 lignes de production instrument\u00e9es (les usines mono-ligne sont exclues pour r\u00e9duire la variance)<\/li>\n<li>Couverture capteur sup\u00e9rieure \u00e0 80% des heures de production (pas de gros trous de donn\u00e9es)<\/li>\n<li>Classification sectorielle v\u00e9rifi\u00e9e contre les d\u00e9clarations entreprise ou attestation client directe<\/li>\n<\/ul>\n<p>Les usines ayant d\u00e9marr\u00e9 un d\u00e9ploiement TeepTrak mais n&#8217;ayant pas atteint 90 jours de capture continue ont \u00e9t\u00e9 exclues. Cela produit un biais de survie vers les d\u00e9ploiements plus matures \u2014 trait\u00e9 quantitativement en Section 5.<\/p>\n<h3>1.3 Distribution g\u00e9ographique et sectorielle<\/h3>\n<table style=\"width:100%;border-collapse:collapse;margin:16px 0;\">\n<tr style=\"background:#232120;color:#FAF8F5;\">\n<th style=\"padding:10px;text-align:left;\">R\u00e9gion<\/th>\n<th style=\"padding:10px;text-align:left;\">Usines<\/th>\n<th style=\"padding:10px;text-align:left;\">Part<\/th>\n<\/tr>\n<tr>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">Europe occidentale (FR, DE, ES, IT, BE, NL)<\/td>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">248<\/td>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">54,7%<\/td>\n<\/tr>\n<tr style=\"background:#F9F9F9;\">\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">Am\u00e9rique du Nord (US, CA, MX)<\/td>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">92<\/td>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">20,3%<\/td>\n<\/tr>\n<tr>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">Asie-Pacifique (CN, JP, KR, IN, AU)<\/td>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">67<\/td>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">14,8%<\/td>\n<\/tr>\n<tr style=\"background:#F9F9F9;\">\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">Europe orientale (PL, CZ, RO, HU)<\/td>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">28<\/td>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">6,2%<\/td>\n<\/tr>\n<tr>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">Am\u00e9rique latine et autres<\/td>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">18<\/td>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\">4,0%<\/td>\n<\/tr>\n<tr>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\"><strong>Total<\/strong><\/td>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\"><strong>453<\/strong><\/td>\n<td style=\"padding:8px 10px;border-bottom:1px solid #E5E5E5;\"><strong>100%<\/strong><\/td>\n<\/tr>\n<\/table>\n<p>R\u00e9partition sectorielle suivant ISIC R\u00e9v. 4 (Classification internationale type des industries, R\u00e9v. 4) : Automobile rang 1 (60 usines), Automobile rang 2\/3 (78), Agroalimentaire (84), Pharmaceutique (47), Plasturgie et composites (61), A\u00e9ronautique (29), Cosm\u00e9tique (35), M\u00e9tallurgie et industrie lourde (33), \u00c9lectronique (26).<\/p>\n<h2>2. R\u00e8gles de calcul du TRS<\/h2>\n<h3>2.1 Formule trois piliers (Nakajima)<\/h3>\n<p>Le TRS est calcul\u00e9 selon la formule trois piliers Nakajima standard :<\/p>\n<p style=\"background:#fff;border:1px solid #E5E5E5;padding:16px;margin:16px 0;border-radius:4px;text-align:center;font-size:18px;\"><strong>TRS = Disponibilit\u00e9 \u00d7 Performance \u00d7 Qualit\u00e9<\/strong><\/p>\n<ul>\n<li><strong>Disponibilit\u00e9<\/strong> = Temps de marche \u00f7 Temps de production planifi\u00e9<\/li>\n<li><strong>Performance<\/strong> = (Quantit\u00e9 totale \u00d7 Cycle nominal) \u00f7 Temps de marche<\/li>\n<li><strong>Qualit\u00e9<\/strong> = Pi\u00e8ces bonnes \u00f7 Quantit\u00e9 totale<\/li>\n<\/ul>\n<h3>2.2 D\u00e9finition du Temps de production planifi\u00e9<\/h3>\n<p>Le Temps de production planifi\u00e9 exclut les fen\u00eatres de non-production programm\u00e9es (arr\u00eats planifi\u00e9s, week-ends sans \u00e9quipe, fermetures de f\u00e9ri\u00e9s). Il inclut :<\/p>\n<ul>\n<li>Heures de production programm\u00e9es par \u00e9quipe<\/li>\n<li>Fen\u00eatres de maintenance pr\u00e9ventive (m\u00e9thode Nakajima \u2014 incluse au d\u00e9nominateur de la Disponibilit\u00e9)<\/li>\n<li>Changements de s\u00e9rie planifi\u00e9s<\/li>\n<li>Fen\u00eatres de pauses op\u00e9rateurs lorsque la ligne est cens\u00e9e tourner<\/li>\n<\/ul>\n<p>Coh\u00e9rent avec la m\u00e9thodologie TPM Nakajima. Les usines utilisant la m\u00e9thode alternative Vorne ou SEMI E10 (o\u00f9 les arr\u00eats planifi\u00e9s sont exclus du d\u00e9nominateur) reporteraient des valeurs de Disponibilit\u00e9 plus \u00e9lev\u00e9es. <strong>Les comparaisons inter-m\u00e9thodes doivent \u00eatre faites avec prudence.<\/strong><\/p>\n<h3>2.3 Calibration du Cycle nominal (P10 soutenu)<\/h3>\n<p>Le Cycle nominal est l&#8217;entr\u00e9e la plus consequente \u2014 de petites erreurs de calibration cr\u00e9ent de grandes distorsions sur la Performance. Le benchmark utilise la <strong>m\u00e9thode P10 soutenu<\/strong> :<\/p>\n<ol>\n<li>Capter la donn\u00e9e temps de cycle par pi\u00e8ce sur 90 jours<\/li>\n<li>Filtrer au top 10% (90\u00e8me percentile, les cycles les plus rapides)<\/li>\n<li>Trouver la plus longue plage soutenue (1 heure ou plus) o\u00f9 les cycles sont rest\u00e9s dans cette bande top 10%<\/li>\n<li>Utiliser le cycle moyen de cette plage soutenue comme Cycle nominal<\/li>\n<\/ol>\n<p>Les valeurs plaque constructeur ne sont explicitement PAS utilis\u00e9es. L&#8217;analyse industrie montre que les valeurs plaque sont 5 \u00e0 15% conservatrices en moyenne, ce qui gonflerait la Performance report\u00e9e. La moyenne historique des cycles n&#8217;est pas utilis\u00e9e non plus \u2014 cette approche int\u00e8gre la lenteur dans la base.<\/p>\n<h3>2.4 D\u00e9finition de la Qualit\u00e9<\/h3>\n<p>Pi\u00e8ces bonnes = pi\u00e8ces passant l&#8217;inspection au premier essai. <strong>Les pi\u00e8ces retouch\u00e9es sont compt\u00e9es en perte Qualit\u00e9<\/strong> \u2014 une pi\u00e8ce n\u00e9cessitant retouche n&#8217;est pas une pi\u00e8ce bonne, car elle a \u00e9chou\u00e9 \u00e0 l&#8217;inspection au premier passage. C&#8217;est plus strict que certaines enqu\u00eates industrie qui comptent les retouches comme bonnes si le contr\u00f4le final passe. Le choix est d\u00e9lib\u00e9r\u00e9 : compter les retouches comme bonnes masque les probl\u00e8mes qualit\u00e9 et le co\u00fbt r\u00e9el des retouches en main-d&#8217;\u0153uvre, temps et mati\u00e8re.<\/p>\n<h2>3. M\u00e9thodologie d&#8217;agr\u00e9gation<\/h2>\n<h3>3.1 TRS au niveau usine<\/h3>\n<p>Le TRS usine est calcul\u00e9 comme la moyenne pond\u00e9r\u00e9e par le temps sur toutes les lignes instrument\u00e9es, pond\u00e9r\u00e9e par le Temps de production planifi\u00e9 par ligne. Les lignes ayant moins de 30 jours de donn\u00e9es sur la p\u00e9riode de reporting sont exclues de l&#8217;agr\u00e9gat usine.<\/p>\n<h3>3.2 M\u00e9dianes et percentiles sectoriels<\/h3>\n<p>Les statistiques sectorielles utilisent le TRS au niveau usine comme observation d&#8217;entr\u00e9e. Valeurs report\u00e9es :<\/p>\n<ul>\n<li><strong>M\u00e9diane (P50)<\/strong> \u2014 point de r\u00e9f\u00e9rence central pour la performance sectorielle typique<\/li>\n<li><strong>Top d\u00e9cile (P90)<\/strong> \u2014 seuil de la performance &#8220;classe mondiale&#8221; intra-secteur<\/li>\n<li><strong>Bottom d\u00e9cile (P10)<\/strong> \u2014 seuil sous lequel l&#8217;opportunit\u00e9 d&#8217;am\u00e9lioration est la plus forte<\/li>\n<\/ul>\n<p>Les moyennes ne sont pas report\u00e9es car les distributions de TRS sont typiquement asym\u00e9triques \u00e0 gauche (longue queue d&#8217;usines \u00e0 faible TRS). Les m\u00e9dianes repr\u00e9sentent mieux la performance typique.<\/p>\n<h3>3.3 Reporting au niveau pays<\/h3>\n<p>Les statistiques au niveau pays ne sont report\u00e9es que lorsque le dataset inclut 8 usines ou plus dans ce pays. Sous ce seuil, l&#8217;\u00e9chantillon est trop petit pour une inf\u00e9rence fiable et induirait le lecteur en erreur.<\/p>\n<h2>4. Le constat de l&#8217;\u00e9cart 13,4 points (validation)<\/h2>\n<p>Pour 152 usines du dataset, \u00e0 la fois des valeurs de TRS auto-d\u00e9clar\u00e9es (issues du reporting management ant\u00e9rieur) et le TRS direct-capteur (depuis le d\u00e9ploiement TeepTrak) sont disponibles pour les 90 premiers jours post-d\u00e9ploiement. Sur ces 152 usines :<\/p>\n<ul>\n<li><strong>TRS direct-capteur m\u00e9dian : 60,4%<\/strong><\/li>\n<li><strong>TRS auto-d\u00e9clar\u00e9 m\u00e9dian : 73,8%<\/strong><\/li>\n<li><strong>\u00c9cart m\u00e9dian : 13,4 points de pourcentage<\/strong><\/li>\n<\/ul>\n<p>L&#8217;\u00e9cart est concentr\u00e9 dans trois zones :<\/p>\n<ol>\n<li><strong>Micro-arr\u00eats (sous 5 minutes)<\/strong> \u2014 les op\u00e9rateurs ne peuvent pas les d\u00e9clarer fiablement sur papier. Sous-comptage m\u00e9dian : 35-50% des minutes d&#8217;arr\u00eat totales.<\/li>\n<li><strong>Pertes de vitesse<\/strong> \u2014 fonctionnement soutenu sous le cycle nominal appara\u00eet identique au fonctionnement \u00e0 cycle nominal sur les relev\u00e9s papier. Sous-comptage m\u00e9dian : 8-12 points de Performance.<\/li>\n<li><strong>Rebuts de red\u00e9marrage<\/strong> \u2014 les pi\u00e8ces produites imm\u00e9diatement apr\u00e8s un arr\u00eat sont souvent mal-cat\u00e9goris\u00e9es en d\u00e9fauts r\u00e9gime \u00e9tabli (Perte 5) plut\u00f4t qu&#8217;en pertes au d\u00e9marrage (Perte 6), gonflant la Qualit\u00e9 et masquant 5-8% de TRS r\u00e9cup\u00e9rable.<\/li>\n<\/ol>\n<p>Cette cohorte de validation 152 usines est elle-m\u00eame une contribution m\u00e9thodologique \u2014 c&#8217;est, \u00e0 la connaissance de TeepTrak, la plus grande comparaison directe publi\u00e9e entre TRS auto-d\u00e9clar\u00e9 et TRS direct-capteur.<\/p>\n<h2>5. Limitations connues<\/h2>\n<p>Le benchmark a plusieurs limitations que les lecteurs doivent consid\u00e9rer lors de l&#8217;interpr\u00e9tation des valeurs :<\/p>\n<h3>5.1 Auto-s\u00e9lection clients<\/h3>\n<p>Toutes les usines du dataset sont des clients TeepTrak. Cela signifie : (a) elles ont d\u00e9cid\u00e9 d&#8217;investir dans le monitoring TRS, sugg\u00e9rant une certaine maturit\u00e9 op\u00e9rationnelle de base ; (b) elles peuvent avoir une motivation TRS sup\u00e9rieure \u00e0 la moyenne. Le dataset ne repr\u00e9sente pas &#8220;tous les industriels&#8221; \u2014 il repr\u00e9sente &#8220;les industriels ayant d\u00e9ploy\u00e9 un monitoring TRS direct-capteur&#8221;.<\/p>\n<h3>5.2 Biais de survie vers les d\u00e9ploiements matures<\/h3>\n<p>La r\u00e8gle minimum 90 jours de capture exclut les usines ayant abandonn\u00e9 les d\u00e9ploiements. Cela biaise le dataset vers les usines ayant compl\u00e9t\u00e9 avec succ\u00e8s le d\u00e9ploiement, ce qui peut corr\u00e9ler avec une discipline op\u00e9rationnelle sup\u00e9rieure \u00e0 la moyenne.<\/p>\n<h3>5.3 Sur-repr\u00e9sentation Europe occidentale<\/h3>\n<p>L&#8217;Europe occidentale repr\u00e9sente 54,7% des usines, refl\u00e9tant l&#8217;origine g\u00e9ographique de TeepTrak et sa base clients. La repr\u00e9sentation Am\u00e9rique du Nord (20,3%) et APAC (14,8%) est significative mais plus faible. Les benchmarks sectoriels doivent \u00eatre consid\u00e9r\u00e9s comme les plus fiables pour les op\u00e9rations europ\u00e9ennes et ajust\u00e9s avec prudence pour les autres r\u00e9gions.<\/p>\n<h3>5.4 Agr\u00e9gation sous-sectorielle<\/h3>\n<p>Les benchmarks sectoriels agr\u00e8gent une diversit\u00e9 consid\u00e9rable au sein de chaque secteur. &#8220;Automobile rang 1&#8221; inclut \u00e0 la fois l&#8217;emboutissage et l&#8217;assemblage final ; &#8220;Pharmaceutique&#8221; inclut \u00e0 la fois les biologiques en petits lots et les formes orales solides en gros volumes. Les chefs d&#8217;usine comparant leur TRS aux benchmarks sectoriels doivent consid\u00e9rer les sp\u00e9cificit\u00e9s sous-sectorielles non captur\u00e9es au niveau ISIC R\u00e9v. 4 utilis\u00e9 ici.<\/p>\n<h3>5.5 Donn\u00e9es mon\u00e9taires et de co\u00fbts<\/h3>\n<p>Lorsque le benchmark reporte des donn\u00e9es de co\u00fbts (par exemple 240 000 \u20ac\/heure de co\u00fbt moyen industrie pour les arr\u00eats), les chiffres sont exprim\u00e9s en euros 2026. Les valeurs en devises locales peuvent diverger.<\/p>\n<h2>6. Reproductibilit\u00e9 et contact<\/h2>\n<p>Le dataset du benchmark est publi\u00e9 sous <a href=\"https:\/\/creativecommons.org\/licenses\/by\/4.0\/\">CC BY 4.0<\/a> \u2014 libre de partage et d&#8217;adaptation avec attribution. Les chercheurs acad\u00e9miques demandant l&#8217;acc\u00e8s aux donn\u00e9es anonymis\u00e9es au niveau usine pour des fins de r\u00e9plication peuvent contacter <a href=\"mailto:research@teeptrak.com\">research@teeptrak.com<\/a>.<\/p>\n<p>Pour citation en contexte acad\u00e9mique et journalistique, utiliser :<\/p>\n<div style=\"background:#232120;color:#FAF8F5;padding:24px;border-radius:6px;margin:24px 0;font-family:'JetBrains Mono',monospace;font-size:13px;\">\n<pre style=\"margin:0;white-space:pre-wrap;word-break:break-word;\">@techreport{teeptrak2026trs,\n  author      = {{TeepTrak Manufacturing Research}},\n  title       = {Benchmark TRS 2026 : Donnees direct-capteur de plus de 450 usines industrielles dans 30 pays},\n  institution = {TeepTrak},\n  year        = {2026},\n  month       = {May},\n  url         = {https:\/\/teeptrak.com\/fr\/benchmark-trs-2026\/},\n  note        = {Methodologie : https:\/\/teeptrak.com\/fr\/methodologie-benchmark-trs-2026\/}\n}<\/pre>\n<\/div>\n<h2>7. Mises \u00e0 jour<\/h2>\n<p>Le benchmark est con\u00e7u comme une publication annuelle. L&#8217;\u00e9dition 2027 incorporera au moins 12 mois suppl\u00e9mentaires de capture et devrait \u00e9largir la repr\u00e9sentation Am\u00e9rique du Nord et APAC. Les mises \u00e0 jour m\u00e9thodologiques entre \u00e9ditions seront document\u00e9es dans un changelog ajout\u00e9 \u00e0 cette page.<\/p>\n<div style=\"background:#fff5f5;border:2px dashed #EB352C;border-radius:8px;padding:28px;margin:32px 0;text-align:center;\">\n<div style=\"font-size:18px;font-weight:bold;color:#232120;margin-bottom:8px;\">Lire le rapport complet du benchmark<\/div>\n<div style=\"font-size:14px;color:#555;margin-bottom:20px;\">M\u00e9dianes sectorielles, top d\u00e9ciles et le constat des 13,4 points en d\u00e9tail<\/div>\n<p><a href=\"\/fr\/benchmark-trs-2026\/\" style=\"display:inline-block;background:#EB352C;color:white;padding:14px 32px;border-radius:4px;text-decoration:none;font-weight:600;\">Voir le Benchmark TRS 2026 \u2192<\/a>\n<\/div>\n<div style=\"background:#F5F5F5;padding:16px;margin:24px 0;border-radius:4px;font-size:14px;color:#666;\">\n<p style=\"margin:0;\"><strong>Citation :<\/strong> TeepTrak Manufacturing Research (2026). <em>Benchmark TRS 2026 \u2014 M\u00e9thodologie.<\/em> https:\/\/teeptrak.com\/fr\/methodologie-benchmark-trs-2026\/. Publi\u00e9 sous CC BY 4.0.<\/p>\n<\/div>\n<p>[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"<p>[et_pb_section fb_built=&#8221;1&#8243; _builder_version=&#8221;4.27&#8243;][et_pb_row][et_pb_column type=&#8221;4_4&#8243;][et_pb_text] Benchmark TRS 2026 \u2014 M\u00e9thodologie Comment le dataset 450+ usines a \u00e9t\u00e9 construit, valid\u00e9 et analys\u00e9. Publi\u00e9 : Mai 2026 Derni\u00e8re revue : Mai 2026 Licence : CC BY 4.0 Auteur : TeepTrak Manufacturing Research R\u00e9sum\u00e9 Le Benchmark TRS 2026 agr\u00e8ge des donn\u00e9es de production direct-capteur issues de 453 usines industrielles [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":92587,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","ai_seo_title":"Benchmark TRS 2026 \u2014 M\u00e9thodologie | TeepTrak","ai_meta_description":"M\u00e9thodologie compl\u00e8te du Benchmark TRS TeepTrak 2026 : 450+ usines, 30 pays, secteurs ISIC R\u00e9v. 4. Donn\u00e9es direct-capteur, calibration P10, validation.","ai_focus_keyword":"m\u00e9thodologie benchmark TRS","footnotes":""},"categories":[101],"tags":[],"class_list":["post-92593","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industrial-performance"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Benchmark TRS 2026 \u2014 M\u00e9thodologie | TeepTrak<\/title>\n<meta name=\"description\" content=\"M\u00e9thodologie compl\u00e8te du Benchmark TRS TeepTrak 2026 : 450+ usines, 30 pays, secteurs ISIC R\u00e9v. 4. 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