{"id":35298,"date":"2026-10-23T11:53:00","date_gmt":"2026-10-23T09:53:00","guid":{"rendered":"https:\/\/www.azzurrodigitale.com\/oee-what-it-is-how-to-calculate-it-and-how-to-improve-it\/"},"modified":"2026-10-28T10:00:18","modified_gmt":"2026-10-28T09:00:18","slug":"oee-what-it-is-how-to-calculate-it-and-how-to-improve-it","status":"publish","type":"post","link":"https:\/\/www.azzurrodigitale.com\/en\/oee-what-it-is-how-to-calculate-it-and-how-to-improve-it\/","title":{"rendered":"OEE: what it is, how to calculate it, and how to improve it"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_89 ez-toc-wrap-left counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Indice dei contenuti<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #21bdff;color:#21bdff\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #21bdff;color:#21bdff\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.azzurrodigitale.com\/en\/oee-what-it-is-how-to-calculate-it-and-how-to-improve-it\/#What_is_OEE_Overall_Equipment_Effectiveness_explained\" >What is OEE? Overall Equipment Effectiveness explained<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.azzurrodigitale.com\/en\/oee-what-it-is-how-to-calculate-it-and-how-to-improve-it\/#OEE_formula_how_to_calculate_OEE_three_factors_one_multiplication\" >OEE formula: how to calculate OEE (three factors, one multiplication)<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.azzurrodigitale.com\/en\/oee-what-it-is-how-to-calculate-it-and-how-to-improve-it\/#OEE_calculation_a_worked_example\" >OEE calculation: a worked example<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.azzurrodigitale.com\/en\/oee-what-it-is-how-to-calculate-it-and-how-to-improve-it\/#OEE_benchmarks_what_is_a_good_OEE_score\" >OEE benchmarks: what is a good OEE score?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.azzurrodigitale.com\/en\/oee-what-it-is-how-to-calculate-it-and-how-to-improve-it\/#The_Six_Big_Losses_Where_Efficiency_Goes\" >The Six Big Losses: Where Efficiency Goes<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.azzurrodigitale.com\/en\/oee-what-it-is-how-to-calculate-it-and-how-to-improve-it\/#Manual_OEE_calculation_vs_OEE_software\" >Manual OEE calculation vs OEE software<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/www.azzurrodigitale.com\/en\/oee-what-it-is-how-to-calculate-it-and-how-to-improve-it\/#How_to_improve_OEE_with_real-time_factory_data\" >How to improve OEE with real-time factory data<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/www.azzurrodigitale.com\/en\/oee-what-it-is-how-to-calculate-it-and-how-to-improve-it\/#From_55_to_80_OEE_what_happens_in_between\" >From 55% to 80% OEE: what happens in between<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/www.azzurrodigitale.com\/en\/oee-what-it-is-how-to-calculate-it-and-how-to-improve-it\/#Frequently_Asked_Questions_FAQ\" >Frequently Asked Questions (FAQ)<\/a><\/li><\/ul><\/nav><\/div>\n\n<p class=\"wp-block-paragraph\"><em>If you work in production, you\u2019ve probably already heard of OEE. Maybe you already calculate it, maybe you see it in monthly reports, or maybe it\u2019s one of your department\u2019s targets. But how often, looking at that number, have you felt it tells you little about what to do to actually improve it?  <\/em><\/p>\n\n\n\n<div style=\"height:60px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">OEE is one of the most cited KPIs in manufacturing. It\u2019s also one of the most misunderstood\u2014not because it\u2019s complicated, but because a number alone isn\u2019t enough. You need to understand what\u2019s behind it.   <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In this article, we start with the basics and move to what matters most: how to use real factory data to stop just measuring OEE and start improving it.<\/p>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"What_is_OEE_Overall_Equipment_Effectiveness_explained\"><\/span><strong>What is OEE? Overall Equipment Effectiveness explained<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>OEE stands for Overall Equipment Effectiveness<\/strong>. It is an index that measures how effectively a plant or machine <strong>is being used compared to its theoretical maximum potential<\/strong>. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In other words: of all the time that machine could be producing, how much is actually used productively and without defects?<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">OEE is expressed as a percentage, <strong>ranging ideally from 0 to 100%<\/strong>. An OEE of 100% means the machine is always producing, at maximum speed, without ever generating defects. In reality, no plant reaches this, and it\u2019s not necessary to do so. But understanding where you stand relative to this benchmark is the first step toward improvement.   <\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>In discrete manufacturing, a world-class OEE is considered to be 85%<\/strong>. The average for factories ranges between 40% and 60%. The gap\u2014often 25\u201330 percentage points\u2014represents a huge amount of latent production capacity that goes unused.  <\/p>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"OEE_formula_how_to_calculate_OEE_three_factors_one_multiplication\"><\/span><strong>OEE formula: how to calculate OEE (three factors, one multiplication)<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">OEE is calculated by multiplying three indices: <strong>Availability<\/strong>, <strong>Performance<\/strong>, and <strong>Quality<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>OEE = Availability \u00d7 Performance \u00d7 Quality<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Each of these three factors captures a different category of production loss. Let\u2019s look at them one by one. <\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Availability<\/strong><\/h4>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Availability = Actual operating time \u00f7 Planned production time<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It measures how much time the machine is actually producing compared to how much it should be. Availability losses are caused by unplanned stoppages: breakdowns, waiting for materials, prolonged setups, or unexpected maintenance. A machine that should run for 8 hours but stops for 2 hours due to a breakdown has an availability of 75%.  <\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Performance<\/strong><\/h4>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Performance = (Units produced \u00f7 Operating time) \u00f7 Ideal speed<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It measures whether the machine, when running, operates at the speed it was designed for. Performance losses are caused by micro-stoppages (short stops that accumulate), reduced cycle speed, or process inefficiencies. A machine that could produce 100 units per hour but produces 80 has a performance of 80%.  <\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Quality<\/strong><\/h4>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Quality = Conforming units \u00f7 Total units produced<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It measures how many of the produced units actually meet the specifications on the first pass (first pass yield). Quality losses include scrap, rework, and defective production during startup. A machine that produces 100 units but rejects 5 has a quality of 95%.  <\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"OEE_calculation_a_worked_example\"><\/span><strong>OEE calculation: a worked example<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Percentages alone don&#8217;t tell you much. Here&#8217;s how to calculate OEE starting from the raw data of an 8-hour shift on a production line.<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Data<\/th><th>Value<\/th><\/tr><\/thead><tbody><tr><td>Shift length<\/td><td>480 min<\/td><\/tr><tr><td>Planned break<\/td><td>30 min<\/td><\/tr><tr><td><strong>Planned production time<\/strong><\/td><td><strong>450 min<\/strong><\/td><\/tr><tr><td>Unplanned downtime (breakdown 20 min + setup 27 min)<\/td><td>47 min<\/td><\/tr><tr><td><strong>Run time<\/strong><\/td><td><strong>403 min<\/strong><\/td><\/tr><tr><td>Ideal cycle time<\/td><td>1 part\/min<\/td><\/tr><tr><td>Total parts produced<\/td><td>350<\/td><\/tr><tr><td>Rejected parts<\/td><td>14<\/td><\/tr><tr><td><strong>Good parts<\/strong><\/td><td><strong>336<\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<ol class=\"wp-block-list\">\n<li><strong>Availability<\/strong> = 403 \u00f7 450 = <strong>89.6%<\/strong><\/li>\n\n\n\n<li><strong>Performance<\/strong> = (350 \u00d7 1 min) \u00f7 403 min = <strong>86.8%<\/strong><\/li>\n\n\n\n<li><strong>Quality<\/strong> = 336 \u00f7 350 = <strong>96.0%<\/strong><\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>OEE = 0.896 \u00d7 0.868 \u00d7 0.960 = 74.7%<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Quick check: good parts \u00d7 ideal cycle time \u00f7 planned production time = 336 \u00f7 450 = 74.7%. The result matches.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">What does this number tell you? Of 450 planned minutes, roughly 336 were fully productive. The other 114 were losses: 47 from downtime, 53 from slow cycles and minor stops, 14 from rejects. That&#8217;s where every improvement plan starts.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Watch out for the multiplicative effect too: a machine with 80% availability, 90% performance and 95% quality has an OEE of 0.80 \u00d7 0.90 \u00d7 0.95 = 68.4%. Three values that look acceptable on their own produce an OEE nearly 17 points below world class: <strong>inefficiencies amplify one another<\/strong>, which is why improving just one factor is not enough.<\/p>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<!-- AzzurroDigitale OEE Calculator \u2013 paste into a \"Custom HTML\" block -->\n<div class=\"adoee\" id=\"adoee\" data-lang=\"en\">\n<style>\n.adoee{--az:#00BDFF;--ink:#212322;--g1:#2E3130;--g2:#6B6F6E;--line:#E3E5E4;--ok:#1FA971;--warn:#F2A900;--bad:#E5484D;\n  font-family:Montserrat,system-ui,sans-serif;color:var(--ink);margin:40px 0;line-height:1.45;box-sizing:border-box}\n.adoee *,.adoee *::before,.adoee *::after{box-sizing:border-box}\n.adoee .ao-card{background:var(--ink);color:#fff;border-radius:24px;padding:28px;position:relative}\n.adoee .ao-dots{position:absolute;top:22px;right:24px;display:flex;gap:6px}\n.adoee .ao-dots 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ao-res\" aria-live=\"polite\">\n      <h4 data-t=\"results\"><\/h4>\n      <div class=\"ao-big\">\n        <svg class=\"ao-gauge\" viewBox=\"0 0 128 128\" role=\"img\" aria-labelledby=\"adoee-gt\">\n          <title id=\"adoee-gt\">OEE<\/title>\n          <circle class=\"bg\" cx=\"64\" cy=\"64\" r=\"54\"\/>\n          <circle class=\"fg\" cx=\"64\" cy=\"64\" r=\"54\" transform=\"rotate(-90 64 64)\" stroke-dasharray=\"339.29\" stroke-dashoffset=\"339.29\"\/>\n          <text class=\"v\" x=\"64\" y=\"70\" text-anchor=\"middle\">\u2013<\/text>\n          <text class=\"s\" x=\"64\" y=\"90\" text-anchor=\"middle\">OEE<\/text>\n        <\/svg>\n        <div><span class=\"ao-level\"><\/span><p class=\"ao-level-d\"><\/p><\/div>\n      <\/div>\n      <div class=\"ao-bars\">\n        <div data-f=\"a\"><div class=\"ao-bar-h\"><span data-t=\"avail\"><\/span><span><b><\/b> <small><\/small><\/span><\/div><div class=\"ao-track\"><div class=\"ao-fill\"><\/div><div class=\"ao-mark\" style=\"left:90%\"><\/div><\/div><\/div>\n        <div data-f=\"p\"><div class=\"ao-bar-h\"><span data-t=\"perf\"><\/span><span><b><\/b> <small><\/small><\/span><\/div><div class=\"ao-track\"><div class=\"ao-fill\"><\/div><div class=\"ao-mark\" style=\"left:95%\"><\/div><\/div><\/div>\n        <div data-f=\"q\"><div class=\"ao-bar-h\"><span data-t=\"qual\"><\/span><span><b><\/b> <small><\/small><\/span><\/div><div class=\"ao-track\"><div class=\"ao-fill\"><\/div><div class=\"ao-mark\" style=\"left:99.9%\"><\/div><\/div><\/div>\n        <div class=\"ao-legend\"><b><\/b><span data-t=\"legend\"><\/span><\/div>\n      <\/div>\n      <div>\n        <p class=\"ao-group-t\" data-t=\"lossT\"><\/p>\n        <div class=\"ao-stack\"><div style=\"background:var(--ink)\" data-s=\"ok\"><\/div><div style=\"background:var(--bad)\" data-s=\"d\"><\/div><div style=\"background:var(--warn)\" data-s=\"s\"><\/div><div style=\"background:var(--az)\" data-s=\"q\"><\/div><\/div>\n        <table 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Averlo in tempo reale, per ogni macchina e turno, \u00e8 ci\u00f2 che fa la differenza.',ctaBtn:'Parla con un esperto',\n      note:'Calcolo indicativo su un singolo turno. Nessun dato inserito viene salvato o inviato.'},\n    en:{pill:'Free tool',title:'OEE Calculator',sub:'Enter one shift\u2019s data from your line: the calculation follows the exact formula explained in this article (Availability \u00d7 Performance \u00d7 Quality). 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No data you enter is stored or sent.'}\n  }[L];\n  function D(s){var x=document.createElement('textarea');x.innerHTML=s;return x.value;}\n  (function W(o){Object.keys(o).forEach(function(k){if(typeof o[k]==='string')o[k]=D(o[k]);else if(o[k]&&typeof o[k]==='object')W(o[k]);});})(T);\n  var DEF={shift:480,breaks:30,down:47,cycle:60,total:350,scrap:14};\n  var loc=L==='en'?'en-GB':'it-IT';\n  function pct(x){return (x*100).toLocaleString(loc,{minimumFractionDigits:1,maximumFractionDigits:1})+'%';}\n  function num(x,d){return x.toLocaleString(loc,{maximumFractionDigits:d||0});}\n  function q(s){return root.querySelector(s);} function qa(s){return root.querySelectorAll(s);}\n  qa('[data-t]').forEach(function(e){var v=T[e.dataset.t]; if(typeof v==='string') e.textContent=v;});\n  var inp={}; qa('input[data-k]').forEach(function(e){inp[e.dataset.k]=e; e.value=DEF[e.dataset.k];});\n  var tracked=false;\n  function ev(n,p){p=p||{};p.calculator_lang=L;try{if(typeof window.gtag==='function'){window.gtag('event',n,p);}else{(window.dataLayer=window.dataLayer||[]).push(Object.assign({event:n},p));}}catch(x){}}\n  var lastBand='';\n  function v(k){var x=parseFloat(String(inp[k].value).replace(',','.')); return isNaN(x)?0:x;}\n  function err(m){var e=q('.ao-err'); e.style.display=m?'block':'none'; e.textContent=m||''; root.querySelector('.ao-res').style.opacity=m&&m!==T.ePerf?'.35':'1';}\n  function calc(){\n    var shift=v('shift'),br=v('breaks'),dn=v('down'),cyc=v('cycle')\/60,tot=v('total'),sc=v('scrap');\n    var planned=shift-br, run=planned-dn, good=tot-sc;\n    q('[data-o=planned]').textContent=num(Math.max(planned,0))+' min';\n    q('[data-o=run]').textContent=num(Math.max(run,0))+' min';\n    q('[data-o=good]').textContent=num(Math.max(good,0))+' '+T.pcs;\n    if(shift<=0||cyc<=0||tot<=0) return err(T.eZero);\n    if(br>=shift) return err(T.eBreaks);\n    if(dn>=planned) return err(T.eDown);\n    if(sc>tot) return err(T.eScrap);\n    var A=run\/planned, P=(tot*cyc)\/run, Q=good\/tot, O=A*P*Q;\n    err(P>1?T.ePerf:'');\n    var Pc=Math.min(P,1);\n    [['a',A,.90],['p',P,.95],['q',Q,.999]].forEach(function(r){var el=q('[data-f='+r[0]+']'); el.querySelector('b').textContent=pct(r[1]); var g=(r[1]-r[2])*100; el.querySelector('small').textContent=(g>=0?'+':D('&#8722;'))+Math.abs(g).toLocaleString(loc,{maximumFractionDigits:1})+' pt '+T.gap; el.querySelector('.ao-fill').style.width=Math.min(r[1]*100,100)+'%';});\n    var lvl=O<.4?0:O<.6?1:O<.85?2:3; lastBand=['0-40','40-60','60-85','85-100'][lvl]; var col=['var(--bad)','var(--warn)','var(--az)','var(--ok)'][lvl];\n    q('.ao-gauge .v').textContent=pct(O).replace(\/([.,]\\d)%\/,'$1%');\n    var fg=q('.ao-gauge .fg'); fg.style.strokeDashoffset=339.29*(1-Math.min(O,1)); fg.style.stroke=col;\n    var lv=q('.ao-level'); lv.textContent=T.lv[lvl][0]; lv.style.background=col; q('.ao-level-d').textContent=T.lv[lvl][1];\n    \/\/ perdite in minuti (stessa logica dell'articolo)\n    var mOk=good*cyc, mDown=dn, mQual=sc*cyc, mSpeed=Math.max(run-tot*cyc,0);\n    var base=planned;\n    q('[data-o=lOk]').textContent=num(mOk)+D(' min &#183; ')+pct(mOk\/base);\n    q('[data-o=lDown]').textContent=num(mDown)+' min';\n    q('[data-o=lSpeed]').textContent=num(mSpeed)+' min';\n    q('[data-o=lQual]').textContent=num(mQual)+' min';\n    var sum=mOk+mDown+mSpeed+mQual;\n    [['ok',mOk],['d',mDown],['s',mSpeed],['q',mQual]].forEach(function(r){q('[data-s='+r[0]+']').style.width=(r[1]\/sum*100)+'%';});\n    var losses=[['a',mDown],['p',mSpeed],['q',mQual]].sort(function(a,b){return b[1]-a[1];});\n    var extra=Math.round((.85*planned)\/cyc-good);\n    q('.ao-insight').innerHTML=T.ins(T.fN[losses[0][0]],num(losses[0][1]),O<.85?extra:0);\n  }\n  qa('input[data-k]').forEach(function(e){e.addEventListener('input',function(){calc(); if(!tracked){tracked=true; ev('oee_calculator_use');}});});\n  q('.ao-reset').addEventListener('click',function(){Object.keys(DEF).forEach(function(k){inp[k].value=DEF[k];}); calc();});\n  q('.ao-btn').addEventListener('click',function(){ev('oee_calculator_cta',{oee_band:lastBand});});\n  calc();\n})();\n<\/script>\n<\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"OEE_benchmarks_what_is_a_good_OEE_score\"><\/span><strong>OEE benchmarks: what is a good OEE score?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>OEE<\/th><th>Level<\/th><th>What it means<\/th><\/tr><\/thead><tbody><tr><td>&lt; 40%<\/td><td>Low<\/td><td>High losses, frequent stops, often manual data collection. Plenty of room for improvement<\/td><\/tr><tr><td>40\u201360%<\/td><td>Typical<\/td><td>Where most discrete manufacturers sit when they start measuring OEE<\/td><\/tr><tr><td>60\u201385%<\/td><td>Good<\/td><td>Processes under control, main losses known and managed<\/td><\/tr><tr><td>\u2265 85%<\/td><td>World class<\/td><td>The historical TPM reference<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">The world-class value comes from Seiichi Nakajima's TPM framework, which breaks it down as follows:<\/p>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><thead><tr><th>Factor<\/th><th>World class<\/th><\/tr><\/thead><tbody><tr><td>Availability<\/td><td>90%<\/td><\/tr><tr><td>Performance<\/td><td>95%<\/td><\/tr><tr><td>Quality<\/td><td>99.9%<\/td><\/tr><tr><td><strong>OEE<\/strong><\/td><td><strong>85%<\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">A word of caution: the most useful benchmark isn't another industry's number. It's your own line's OEE over time. Comparing different machines, or calculating OEE with different rules across departments, leads to the wrong conclusions.<\/p>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"The_Six_Big_Losses_Where_Efficiency_Goes\"><\/span><strong>The Six Big Losses: Where Efficiency Goes<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Behind the three OEE factors lie what the <strong>TPM (Total Productive Maintenance) methodology<\/strong> calls the Six Big Losses. Understanding them is essential because every improvement effort must begin by identifying which specific loss needs to be reduced. <\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>Breakdowns (Impact: Availability)<\/strong> \u2014 unplanned stops due to equipment failure or malfunctions.<\/li>\n\n\n\n<li><strong>Setup and Adjustments (Impact: Availability)<\/strong> \u2014 production changeover times, tooling, and warm-up periods.<\/li>\n\n\n\n<li><strong>Minor Stoppages (Impact: Performance)<\/strong> \u2014 short and frequent stops, often not recorded manually. Learn more in our guide to <a href=\"https:\/\/www.azzurrodigitale.com\/en\/micro-machine-downtime-oee\/\">micro machine downtime<\/a>.<\/li>\n\n\n\n<li><strong>Reduced Speed (Impact: Performance)<\/strong> \u2014 equipment running, but below the ideal cycle time.<\/li>\n\n\n\n<li><strong>Startup Rejects (Impact: Quality)<\/strong> \u2014 non-compliant parts produced during the startup or production changeover phase.<\/li>\n\n\n\n<li><strong>Production Rejects (Impact: Quality)<\/strong> \u2014 scrap and rework occurring during steady-state production.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Most factories that measure OEE manually fail to distinguish between minor stoppages and reduced speed. Both impact performance, but the causes and solutions are completely different. <\/p>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Manual_OEE_calculation_vs_OEE_software\"><\/span><strong>Manual OEE calculation vs OEE software<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Many manufacturing companies still calculate OEE by collecting data manually: operators note down stops on a sheet, the department head enters them into Excel at the end of the shift, and someone aggregates them into a weekly report. The result often arrives the next day or on the Monday of the following week. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This approach has three structural limitations that make the data nearly unusable for improvement:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Latency: by the time the data is available, the problem that generated it is already in the past. It is impossible to intervene in real time. <\/li>\n\n\n\n<li><strong>Insufficient granularity<\/strong>: minor stoppages, often the most significant loss category, are almost never recorded because the operator does not note them down (they last 30 seconds, then the machine restarts).<\/li>\n\n\n\n<li><strong>Subjectivity<\/strong>: the categorization of causes depends on who fills out the form. The same stoppage is classified differently by different operators. <\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">The result? An OEE that measures but does not explain. It is often used more as a performance indicator in executive reports than as an operational lever for improvement.  <\/p>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"How_to_improve_OEE_with_real-time_factory_data\"><\/span><strong>How to improve OEE with real-time factory data<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>The shift in quality occurs when OEE is calculated automatically<\/strong>, using data generated directly by the machines. Not from the operator taking notes, but from the system detecting the data.<br>Would you like me to translate any further sections of this text on OEE? <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This changes everything. Not only the accuracy of the data, but the use that can be made of it. <\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Real-time data: from historical OEE to live OEE<\/strong><\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">With machine interconnection, every cycle, every stoppage, and every speed variation is recorded automatically. OEE is no longer a number from the day before: it is a live indicator, visible on operational dashboards, allowing department heads to intervene during the shift. <\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>From average to detail: OEE by machine, shift, operator.<\/strong><\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">When data is collected automatically, it is possible to break down OEE at a granular level: not just the average OEE of the department, but the OEE of every single machine, every shift, and every product type. <strong>This granularity is what transforms the KPI into a diagnostic tool<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Example: if the OEE of the night shift is systematically 8 points lower than the day shift, there is something to investigate (operator training, maintenance conditions, different setups). An aggregated OEE would never reveal this.<br>Would you like me to translate the next section or focus on a specific OEE component? <\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Analysis of causes: from losses to actions.<\/strong><\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">The system that automatically records downtime can also categorize and aggregate it with the respective causes. The result is immediate: <strong>20% of the causes generate 80% of the losses<\/strong>. You intervene on those specifically, rather than on everything indiscriminately.  <\/p>\n\n\n\n<div style=\"height:20px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>The role of the MES <\/strong><\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">An <strong><a href=\"https:\/\/www.azzurrodigitale.com\/en\/technologies\/digital-shopfloor\/\">MES software<\/a><\/strong> with a machine monitoring module is the tool that enables this level of analysis. Integrated with PLCs and machine control systems, it automatically collects cycle data, calculates OEE in real time, and provides production managers with the information needed to make decisions. To understand what a MES does in detail, read our guide to the <a href=\"https:\/\/www.azzurrodigitale.com\/en\/mes-software-what-it-is-how-it-works-in-production\/\">MES system in production<\/a>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">It is not a solution reserved for large plants. Today, thanks to IoT gateways and standard connectors, <strong>it is possible to connect even legacy machines without replacing them<\/strong>, and start measuring OEE automatically in a relatively short time. <\/p>\n\n\n\n<div style=\"height:30px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"From_55_to_80_OEE_what_happens_in_between\"><\/span><strong>From 55% to 80% OEE: what happens in between<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Raising OEE from 55% to 80% is not a one-off operation. It is a journey that typically develops in phases, each of which requires data, analysis, and targeted interventions. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Phase 1 \u2014 Measure accurately.<\/strong> Before taking action, you need reliable data. 70% of companies starting an OEE improvement project discover that the actual value is significantly different from what was previously thought. Often, it is lower.  <\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Phase 2 \u2014 Identify dominant losses.<\/strong> With automatic data and Pareto analysis, the 2\u20133 causes that alone explain most of the gap are identified. They are almost always different from what was assumed. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Phase 3 \u2014 Targeted intervention.<\/strong> Reducing setup times using the SMED methodology, improving preventive maintenance on the machines with the most failures, and standardizing startup procedures to reduce initial scrap. Every intervention is data-driven, not based on intuition. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Phase 4 \u2014 Monitor and Stabilize.<\/strong> Improving OEE is not a one-time project. It is a continuous cycle: measure, analyze, intervene, verify. The digital system that made measurement possible also becomes the tool for monitoring the stability of results over time.  <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">An increase of 10 OEE points on a production line often equates to an additional production capacity of 15\u201320%, without investing in new machinery. It is the most immediate and least expensive lever for increasing productivity. <\/p>\n\n\n\n<div style=\"height:40px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"Frequently_Asked_Questions_FAQ\"><\/span><strong>Frequently Asked Questions (FAQ)<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What does OEE mean?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">OEE stands for Overall Equipment Effectiveness. It is a percentage that measures how productively a machine or line is used compared with its theoretical potential, taking into account downtime, speed and scrap.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>How is OEE calculated?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">OEE is obtained by multiplying three factors: Availability \u00d7 Performance \u00d7 Quality. For example, with 89.6% availability, 86.8% performance and 96% quality, OEE is 74.7%.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What is a good OEE value?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The world-class benchmark in discrete manufacturing is 85%, while most plants sit between 40% and 60%. The most useful reference, however, is the trend of the same line's OEE over time.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>What are the six big losses that reduce OEE?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">According to TPM methodology they are breakdowns, setups and adjustments, minor stops, reduced speed, startup rejects and production rejects. Each one affects availability, performance or quality.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Why should OEE be calculated automatically?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Manual data collection arrives late, misses minor stops and depends on who fills in the data. A system connected to the machines, such as a MES, calculates OEE in real time and lets you analyse it by machine, shift and product.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>OEE measures the actual efficiency of your equipment. But measuring it manually is of little use. Discover how to calculate it automatically and use it effectively to improve production.  <\/p>\n","protected":false},"author":2,"featured_media":37204,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[159,160],"tags":[],"class_list":["post-35298","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-ai-en","category-digital-transformation-en"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>OEE Formula: How to Calculate OEE (With Example)<\/title>\n<meta name=\"description\" content=\"What OEE is, the OEE formula and equation explained step by step with a worked calculation, plus benchmarks to see how your line really performs.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link 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