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input[type=range]::-moz-range-thumb{width:20px;height:20px;border-radius:50%;background:#EB352C;border:none;cursor:pointer}<\/style>\n<div style=\"position:relative;width:100vw;margin-left:calc(50% - 50vw);overflow-x:clip;\">\n<div class=\"ttpl\">\n<div class=\"topbar\">\ud83d\udc49 <b>Free 60-day POC<\/b> \u2014 one pilot line. If we don&#8217;t find 10% hidden losses, you pay nothing. <a href=\"#demo\">Get started \u2192<\/a><\/div>\n<nav class=\"subnav\">\n<div class=\"wrap\">\n    <span class=\"pname\">Perf<b>Trak<\/b><\/span><br \/>\n    <a class=\"jump\" href=\"#how\">How it works<\/a><br \/>\n    <a class=\"jump\" href=\"#action\">Product in action<\/a><br \/>\n    <a class=\"jump\" href=\"#operators\">For operators<\/a><br \/>\n    <a class=\"jump\" href=\"#install\">Installation<\/a><br \/>\n    <a class=\"jump\" href=\"#roi\">ROI<\/a><br \/>\n    <a class=\"jump\" href=\"#faq\">FAQ<\/a><br \/>\n    <a class=\"btn btn-red\" href=\"#demo\">Book a demo<\/a>\n  <\/div>\n<\/nav>\n<p><!-- HERO --><\/p>\n<div class=\"hero\">\n<div class=\"wrap\">\n<div>\n      <span class=\"plogo\"><span class=\"pin\">P<\/span>Machine Learning \u00b7 Predictive anomaly detection<\/span><\/p>\n<h1>See the loss coming.<!\u2013- [et_pb_br_holder] -\u2013>Predict <span style=\"color:#FF674C\">deviations before they cost you.<\/span><\/h1>\n<pee class=\"sub\">TeepTrak&#8217;s Machine Learning layer learns what normal looks like on your lines and flags anomalies before they turn into downtime or scrap \u2014 surfacing patterns no human has time to find.<\/pee>\n<div class=\"hero-checks\">\n<div><span class=\"ck\">\u2714<\/span><span><b>Built on your TeepTrak data<\/b> \u2014 no new sensors, no separate data project<\/span><\/div>\n<div><span class=\"ck\">\u2714<\/span><span><b>Learns from day one<\/b> \u2014 trains on the history you already have<\/span><\/div>\n<div><span class=\"ck\">\u2714<\/span><span><b>Explainable, not a black box<\/b> \u2014 every flag comes with its likely cause<\/span><\/div>\n<\/p><\/div>\n<div class=\"hero-ctas\">\n        <a class=\"btn btn-red\" href=\"#demo\">\ud83d\udcc5 Book my demo<\/a><br \/>\n        <a class=\"btn btn-ghost on-dark\" href=\"#roi\">Spot my hidden patterns<\/a>\n      <\/div>\n<div class=\"trustline\"><span class=\"stars\">\u2605\u2605\u2605\u2605\u2605<\/span> <span><b style=\"color:#fff\">450+ factories<\/b> \u00b7 30+ countries \u00b7 4.7\/5 on G2 &amp; Capterra<\/span><\/div>\n<\/p><\/div>\n<div class=\"dash-stack\">\n<div class=\"float-card float-gain\"><small>OEE \u2014 12 WEEKS<\/small><b>+11.8 pts<\/b><span style=\"font-size:11px;color:var(--slate)\">since Machine Learning go-live<\/span><\/div>\n<div class=\"panel\">\n<div class=\"panel-hd\">\n          <span class=\"dot\" style=\"background:#FC5753\"><\/span><span class=\"dot\" style=\"background:#FDBC40\"><\/span><span class=\"dot\" style=\"background:#33C748\"><\/span><br \/>\n          <span class=\"url\">app.teeptrak.com\/perftrak \u00b7 Machining line 1<\/span><br \/>\n          <span class=\"live\">LIVE<\/span>\n        <\/div>\n<div class=\"panel-bd\">\n<div class=\"kpi-row\">\n<div class=\"kpi\"><small>OEE \u2014 shift<\/small><b>78.4%<\/b> <span class=\"up\">\u25b2 2.4<\/span><\/div>\n<div class=\"kpi\"><small>Availability<\/small><b>88.2%<\/b> <span class=\"up\">\u25b2 1.1<\/span><\/div>\n<div class=\"kpi\"><small>Performance<\/small><b>91.5%<\/b> <span class=\"down\">\u25bc 0.6<\/span><\/div>\n<div class=\"kpi\"><small>Quality<\/small><b>97.1%<\/b> <span class=\"up\">\u25b2 0.3<\/span><\/div>\n<\/p><\/div>\n<div class=\"sec-label\">Machine timeline \u2014 06:00 \u2192 now<\/div>\n<div class=\"tl\">\n            <i style=\"width:16%;background:#2ECC71\"><\/i><i style=\"width:3%;background:#E74C3C\"><\/i><i style=\"width:13%;background:#2ECC71\"><\/i><i style=\"width:6%;background:#F5A623\"><\/i><i style=\"width:9%;background:#2ECC71\"><\/i><i style=\"width:5%;background:#E74C3C\"><\/i><i style=\"width:21%;background:#2ECC71\"><\/i><i style=\"width:4%;background:#F5A623\"><\/i><i style=\"width:2%;background:#E74C3C\"><\/i><i style=\"width:21%;background:#2ECC71\"><\/i>\n          <\/div>\n<div class=\"tl-leg\"><span><i style=\"background:#2ECC71\"><\/i>Running<\/span><span><i style=\"background:#E74C3C\"><\/i>Stop \u2014 qualified<\/span><span><i style=\"background:#F5A623\"><\/i>Slow cycle<\/span><\/div>\n<div class=\"sec-label\" style=\"margin-top:14px\">Pareto of stop causes \u2014 today<\/div>\n<div class=\"barlist\">\n<div class=\"row\"><span>Tool change<\/span><\/p>\n<div class=\"track\">\n<div class=\"fill red\" style=\"width:84%\"><\/div>\n<\/div>\n<p><span class=\"val\">18m<\/span><\/div>\n<div class=\"row\"><span>Material wait<\/span><\/p>\n<div class=\"track\">\n<div class=\"fill red\" style=\"width:56%\"><\/div>\n<\/div>\n<p><span class=\"val\">12m<\/span><\/div>\n<div class=\"row\"><span>Micro-stops<\/span><\/p>\n<div class=\"track\">\n<div class=\"fill amb\" style=\"width:42%\"><\/div>\n<\/div>\n<p><span class=\"val\">9m<\/span><\/div>\n<div class=\"row\"><span>Misfeed<\/span><\/p>\n<div class=\"track\">\n<div class=\"fill amb\" style=\"width:28%\"><\/div>\n<\/div>\n<p><span class=\"val\">6m<\/span><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"float-card float-alert\"><span class=\"ic\">!<\/span><span><b>Stop detected \u2014 14:32<\/b><!\u2013- [et_pb_br_holder] -\u2013><span style=\"color:var(--slate)\">Cause qualified by operator: tool change \u00b7 4m 12s<\/span><\/span><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/div>\n<p><!-- LOGOS --><\/p>\n<div class=\"logos\">\n<div class=\"wrap\">\n    <pee>Machine Learning runs in plants of<\/pee>\n<div class=\"logo-row\"><img decoding=\"async\" src=\"https:\/\/cdn.brandfetch.io\/stellantis.com\/w\/160\/h\/48\/fallback\/transparent\/type\/logo?c=1idvhKC37JmLVV0f_XU\" alt=\"stellantis\" style=\"height:30px;width:auto;filter:grayscale(100%);opacity:.55;\"><img decoding=\"async\" src=\"https:\/\/cdn.brandfetch.io\/alstom.com\/w\/160\/h\/48\/fallback\/transparent\/type\/logo?c=1idvhKC37JmLVV0f_XU\" alt=\"alstom\" style=\"height:30px;width:auto;filter:grayscale(100%);opacity:.55;\"><img decoding=\"async\" src=\"https:\/\/cdn.brandfetch.io\/thalesgroup.com\/w\/160\/h\/48\/fallback\/transparent\/type\/logo?c=1idvhKC37JmLVV0f_XU\" alt=\"thalesgroup\" style=\"height:30px;width:auto;filter:grayscale(100%);opacity:.55;\"><img decoding=\"async\" src=\"https:\/\/cdn.brandfetch.io\/safran.com\/w\/160\/h\/48\/fallback\/transparent\/type\/logo?c=1idvhKC37JmLVV0f_XU\" alt=\"safran\" style=\"height:30px;width:auto;filter:grayscale(100%);opacity:.55;\"><img decoding=\"async\" src=\"https:\/\/cdn.brandfetch.io\/valeo.com\/w\/160\/h\/48\/fallback\/transparent\/type\/logo?c=1idvhKC37JmLVV0f_XU\" alt=\"valeo\" style=\"height:30px;width:auto;filter:grayscale(100%);opacity:.55;\"><img decoding=\"async\" src=\"https:\/\/cdn.brandfetch.io\/saint-gobain.com\/w\/160\/h\/48\/fallback\/transparent\/type\/logo?c=1idvhKC37JmLVV0f_XU\" alt=\"saint-gobain\" style=\"height:30px;width:auto;filter:grayscale(100%);opacity:.55;\"><img decoding=\"async\" src=\"https:\/\/cdn.brandfetch.io\/danone.com\/w\/160\/h\/48\/fallback\/transparent\/type\/logo?c=1idvhKC37JmLVV0f_XU\" alt=\"danone\" style=\"height:30px;width:auto;filter:grayscale(100%);opacity:.55;\"><img decoding=\"async\" src=\"https:\/\/cdn.brandfetch.io\/continental.com\/w\/160\/h\/48\/fallback\/transparent\/type\/logo?c=1idvhKC37JmLVV0f_XU\" alt=\"continental\" style=\"height:30px;width:auto;filter:grayscale(100%);opacity:.55;\"><img decoding=\"async\" src=\"https:\/\/cdn.brandfetch.io\/hutchinson.com\/w\/160\/h\/48\/fallback\/transparent\/type\/logo?c=1idvhKC37JmLVV0f_XU\" alt=\"hutchinson\" style=\"height:30px;width:auto;filter:grayscale(100%);opacity:.55;\"><\/div>\n<\/p><\/div>\n<\/div>\n<p><!-- OUTCOMES --><\/p>\n<section>\n<div class=\"wrap\">\n<div style=\"max-width:720px\">\n      <span class=\"eyebrow\">Why Machine Learning<\/span><\/p>\n<h2>The signal is already in your data. Machine Learning finds it before you feel it.<\/h2>\n<\/p><\/div>\n<div class=\"out-grid\">\n<div class=\"out-card reveal\">\n<div class=\"ic\">\ud83d\udd0d<\/div>\n<p>        <span class=\"n\">Learn<\/span><\/p>\n<h3>It learns your normal<\/h3>\n<pee>The model studies each line&#8217;s real rhythm \u2014 cycle times, stops, parameters and quality \u2014 and builds a living baseline of what good actually looks like.<\/pee>\n      <\/div>\n<div class=\"out-card reveal\">\n<div class=\"ic\">\ud83d\udc46<\/div>\n<p>        <span class=\"n\">Predict<\/span><\/p>\n<h3>It flags the abnormal early<\/h3>\n<pee>Drift, creeping micro-stops, an emerging quality pattern \u2014 the model raises it while there is still time to act, not in next month&#8217;s report.<\/pee>\n      <\/div>\n<div class=\"out-card reveal\">\n<div class=\"ic\">\ud83d\udcc8<\/div>\n<p>        <span class=\"n\">Explain<\/span><\/p>\n<h3>With the likely cause attached<\/h3>\n<pee>A live Pareto of losses by line, shift and cause. Your morning meeting starts from the same facts \u2014 and your CI team attacks the biggest loss first.<\/pee>\n      <\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/section>\n<p><!-- HOW IT WORKS --><\/p>\n<section class=\"how\" id=\"how\">\n<div class=\"wrap\">\n<div style=\"text-align:center;max-width:680px;margin:0 auto\">\n      <span class=\"eyebrow\" style=\"justify-content:center\">Operating principle<\/span><\/p>\n<h2>How Machine Learning works<\/h2>\n<pee class=\"sub\" style=\"margin:18px auto 0\">Three steps from your existing data to an early warning you can act on.<\/pee>\n    <\/div>\n<div class=\"steps\">\n<div class=\"step reveal\">\n        <span class=\"num\">1<\/span><\/p>\n<h3>Feed it your data<\/h3>\n<pee>Machine Learning runs on top of your existing TeepTrak data \u2014 OEE, stops, cycles, parameters and quality. Nothing new to install.<\/pee>\n<div class=\"connect-opts\"><span>\ud83d\udcca OEE &amp; stops<\/span><span>\ud83d\udcc8 Cycle times<\/span><span>\ud83e\uddea Quality &amp; parameters<\/span><\/div>\n<p>        <span class=\"t\">&lt; 1 hour per machine<\/span>\n      <\/div>\n<div class=\"step reveal\">\n        <span class=\"num\">2<\/span><\/p>\n<h3>Operators qualify causes<\/h3>\n<pee>When the machine stops, the tablet asks why. The operator picks from your loss tree \u2014 two taps and production continues.<\/pee>\n        <span class=\"t\">2 taps, zero typing<\/span>\n      <\/div>\n<div class=\"step reveal\">\n        <span class=\"num\">3<\/span><\/p>\n<h3>Supervise in real time<\/h3>\n<pee>Consolidated live dashboards: OEE by line, Pareto of causes, shift reports, smartphone alerts, raw-data APIs for your BI.<\/pee>\n        <span class=\"t\">Machine \u2192 plant \u2192 group<\/span>\n      <\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/section>\n<p><!-- PRODUCT IN ACTION --><\/p>\n<section id=\"action\">\n<div class=\"wrap\">\n    <span class=\"eyebrow\">Product in action<\/span><\/p>\n<h2>The supervision platform, exactly as your team will see it<\/h2>\n<div class=\"tabs-bar\">\n      <button class=\"tab-btn active\" data-tab=\"t1\">Live workshop<\/button><br \/>\n      <button class=\"tab-btn\" data-tab=\"t2\">Pareto analysis<\/button><br \/>\n      <button class=\"tab-btn\" data-tab=\"t3\">Shift reports<\/button><br \/>\n      <button class=\"tab-btn\" data-tab=\"t4\">Smartphone alerts<\/button>\n    <\/div>\n<div class=\"tab-pane active\" id=\"t1\">\n<div>\n<h3>Every line, live, on one screen<\/h3>\n<pee class=\"sub\" style=\"font-size:15.5px\">Walk into the workshop \u2014 or open a browser anywhere \u2014 and see machine status, OEE and current losses update in real time.<\/pee>\n<div class=\"feats\">\n<div><span class=\"ck\">\u2714<\/span>Machine status &amp; OEE by line, refreshed live<\/div>\n<div><span class=\"ck\">\u2714<\/span>Drill down: plant \u2192 workshop \u2192 line \u2192 machine<\/div>\n<div><span class=\"ck\">\u2714<\/span>Spot a red line before it costs you the shift<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"panel\">\n<div class=\"panel-hd\"><span class=\"dot\" style=\"background:#FC5753\"><\/span><span class=\"dot\" style=\"background:#FDBC40\"><\/span><span class=\"dot\" style=\"background:#33C748\"><\/span><span class=\"url\">Live workshop \u2014 all lines<\/span><span class=\"live\">LIVE<\/span><\/div>\n<div class=\"panel-bd\">\n<div class=\"barlist\">\n<div class=\"row\"><span>Machining 1<\/span><\/p>\n<div class=\"track\">\n<div class=\"fill\" style=\"width:92%\"><\/div>\n<\/div>\n<p><span class=\"val\">92%<\/span><\/div>\n<div class=\"row\"><span>Machining 2<\/span><\/p>\n<div class=\"track\">\n<div class=\"fill\" style=\"width:85%\"><\/div>\n<\/div>\n<p><span class=\"val\">85%<\/span><\/div>\n<div class=\"row\"><span>Assembly 1<\/span><\/p>\n<div class=\"track\">\n<div class=\"fill amb\" style=\"width:76%\"><\/div>\n<\/div>\n<p><span class=\"val\">76%<\/span><\/div>\n<div class=\"row\"><span>Assembly 2<\/span><\/p>\n<div class=\"track\">\n<div class=\"fill\" style=\"width:87%\"><\/div>\n<\/div>\n<p><span class=\"val\">87%<\/span><\/div>\n<div class=\"row\"><span>Packaging 3<\/span><\/p>\n<div class=\"track\">\n<div class=\"fill red\" style=\"width:64%\"><\/div>\n<\/div>\n<p><span class=\"val\">64%<\/span><\/div>\n<\/p><\/div>\n<div class=\"sec-label\" style=\"margin-top:14px\">Current status<\/div>\n<div style=\"display:flex;gap:8px;flex-wrap:wrap\">\n            <span style=\"font-size:11.5px;font-weight:700;background:#E6F6EC;color:var(--green);border-radius:7px;padding:5px 11px\">\u25cf 4 running<\/span><br \/>\n            <span style=\"font-size:11.5px;font-weight:700;background:var(--red-soft);color:var(--red);border-radius:7px;padding:5px 11px\">\u25cf 1 stopped \u2014 cause: misfeed<\/span>\n          <\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"tab-pane\" id=\"t2\">\n<div>\n<h3>The Pareto that builds itself<\/h3>\n<pee class=\"sub\" style=\"font-size:15.5px\">Every qualified stop feeds the loss tree. By Friday you know your top three losses for the week \u2014 by line, shift, product or team.<\/pee>\n<div class=\"feats\">\n<div><span class=\"ck\">\u2714<\/span>Pareto of stop causes, any period, any scope<\/div>\n<div><span class=\"ck\">\u2714<\/span>Filter by machine, product, shift or team<\/div>\n<div><span class=\"ck\">\u2714<\/span>Export to Excel or feed your BI via API<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"panel\">\n<div class=\"panel-hd\"><span class=\"dot\" style=\"background:#FC5753\"><\/span><span class=\"dot\" style=\"background:#FDBC40\"><\/span><span class=\"dot\" style=\"background:#33C748\"><\/span><span class=\"url\">Pareto \u2014 week 24 \u00b7 Machining 1<\/span><\/div>\n<div class=\"panel-bd\">\n<div class=\"barlist\" style=\"gap:10px\">\n<div class=\"row\"><span>Changeover<\/span><\/p>\n<div class=\"track\" style=\"height:13px\">\n<div class=\"fill red\" style=\"width:88%\"><\/div>\n<\/div>\n<p><span class=\"val\">3.4h<\/span><\/div>\n<div class=\"row\"><span>Micro-stops<\/span><\/p>\n<div class=\"track\" style=\"height:13px\">\n<div class=\"fill red\" style=\"width:62%\"><\/div>\n<\/div>\n<p><span class=\"val\">2.4h<\/span><\/div>\n<div class=\"row\"><span>Material wait<\/span><\/p>\n<div class=\"track\" style=\"height:13px\">\n<div class=\"fill amb\" style=\"width:47%\"><\/div>\n<\/div>\n<p><span class=\"val\">1.8h<\/span><\/div>\n<div class=\"row\"><span>Tool break<\/span><\/p>\n<div class=\"track\" style=\"height:13px\">\n<div class=\"fill amb\" style=\"width:29%\"><\/div>\n<\/div>\n<p><span class=\"val\">1.1h<\/span><\/div>\n<div class=\"row\"><span>No operator<\/span><\/p>\n<div class=\"track\" style=\"height:13px\">\n<div class=\"fill\" style=\"width:18%\"><\/div>\n<\/div>\n<p><span class=\"val\">0.7h<\/span><\/div>\n<\/p><\/div>\n<div style=\"margin-top:16px;background:#F5F6F5;border:1px solid var(--line);border-radius:10px;padding:12px 14px;font-size:12.5px;color:var(--slate)\"><b style=\"color:var(--ink)\">Insight:<\/b> changeovers = 36% of losses this week. A 20% SMED gain on this line \u2248 <b style=\"color:var(--green)\">41 production hours \/ year<\/b>.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"tab-pane\" id=\"t3\">\n<div>\n<h3>Shift reports, written automatically<\/h3>\n<pee class=\"sub\" style=\"font-size:15.5px\">Production counts, OEE, top losses and scrap \u2014 compiled and sent at end of shift. No more Sunday-night Excel.<\/pee>\n<div class=\"feats\">\n<div><span class=\"ck\">\u2714<\/span>Automatic production &amp; count reports<\/div>\n<div><span class=\"ck\">\u2714<\/span>Performance history by machine, line, team<\/div>\n<div><span class=\"ck\">\u2714<\/span>Ready for ISO 9001 and customer audits<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"panel\">\n<div class=\"panel-hd\"><span class=\"dot\" style=\"background:#FC5753\"><\/span><span class=\"dot\" style=\"background:#FDBC40\"><\/span><span class=\"dot\" style=\"background:#33C748\"><\/span><span class=\"url\">Shift report \u2014 morning \u00b7 auto-generated 14:05<\/span><\/div>\n<div class=\"panel-bd\">\n<div class=\"kpi-row\">\n<div class=\"kpi\"><small>OEE<\/small><b>78.4%<\/b><\/div>\n<div class=\"kpi\"><small>Good parts<\/small><b>4,812<\/b><\/div>\n<div class=\"kpi\"><small>Scrap<\/small><b>96<\/b><\/div>\n<div class=\"kpi\"><small>Stops<\/small><b>11<\/b><\/div>\n<\/p><\/div>\n<div class=\"sec-label\">OEE \u2014 last 10 shifts<\/div>\n<p>          <svg viewBox=\"0 0 320 70\" style=\"width:100%;height:70px\" preserveAspectRatio=\"none\">\n            <line x1=\"0\" y1=\"18\" x2=\"320\" y2=\"18\" stroke=\"#EBEBEB\" stroke-width=\"1\" stroke-dasharray=\"4 4\"\/>\n            <text x=\"4\" y=\"14\" font-size=\"8\" fill=\"#8B8885\" font-weight=\"700\">target 80%<\/text>\n            <path d=\"M0,52 L36,48 L72,50 L108,42 L144,44 L180,36 L216,32 L252,28 L288,24 L320,20\" fill=\"none\" stroke=\"#2ECC71\" stroke-width=\"2.5\" stroke-linecap=\"round\"\/>\n            <circle cx=\"320\" cy=\"20\" r=\"4\" fill=\"#2ECC71\"\/>\n          <\/svg><\/p>\n<div style=\"font-size:12px;color:var(--slate);margin-top:8px\">\ud83d\udce7 Sent automatically to: production manager \u00b7 shift leaders \u00b7 CI team<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"tab-pane\" id=\"t4\">\n<div>\n<h3>Know the moment a line goes down<\/h3>\n<pee class=\"sub\" style=\"font-size:15.5px\">Configurable alerts to any smartphone \u2014 machine stopped, OEE under threshold, changeover over target. React in minutes, not at the morning meeting.<\/pee>\n<div class=\"feats\">\n<div><span class=\"ck\">\u2714<\/span>Instant push alerts on stop or deviation<\/div>\n<div><span class=\"ck\">\u2714<\/span>Thresholds per machine, line or product<\/div>\n<div><span class=\"ck\">\u2714<\/span>Escalation rules \u2014 operator \u2192 leader \u2192 manager<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"panel\" style=\"max-width:340px;margin:0 auto\">\n<div class=\"panel-hd\"><span class=\"dot\" style=\"background:#FC5753\"><\/span><span class=\"dot\" style=\"background:#FDBC40\"><\/span><span class=\"dot\" style=\"background:#33C748\"><\/span><span class=\"url\">TeepTrak mobile<\/span><span class=\"live\">LIVE<\/span><\/div>\n<div class=\"panel-bd\" style=\"display:grid;gap:10px\">\n<div style=\"border-left:4px solid #E74C3C;background:#FBEAE7;border-radius:9px;padding:11px 13px;font-size:12.5px\"><b>\ud83d\udd34 Machine stopped \u2014 Packaging 3<\/b><!\u2013- [et_pb_br_holder] -\u2013><span style=\"color:var(--slate)\">14:32 \u00b7 running 0 min \u00b7 no cause yet<\/span><\/div>\n<div style=\"border-left:4px solid var(--amber);background:#FDF3DF;border-radius:9px;padding:11px 13px;font-size:12.5px\"><b>\ud83d\udfe0 Changeover over target \u2014 Assembly 2<\/b><!\u2013- [et_pb_br_holder] -\u2013><span style=\"color:var(--slate)\">14:18 \u00b7 22 min vs 15 min target<\/span><\/div>\n<div style=\"border-left:4px solid var(--green);background:#E6F6EC;border-radius:9px;padding:11px 13px;font-size:12.5px\"><b>\ud83d\udfe2 Back to target \u2014 Machining 1<\/b><!\u2013- [et_pb_br_holder] -\u2013><span style=\"color:var(--slate)\">13:55 \u00b7 OEE 92% \u00b7 shift on track<\/span><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/section>\n<p><!-- OPERATOR TABLET --><\/p>\n<section class=\"tablet-sec\" id=\"operators\">\n<div class=\"wrap\">\n<div>\n      <span class=\"eyebrow\" style=\"color:#FF674C\">Built for your team<\/span><\/p>\n<h2>Insight, not a black box.<\/h2>\n<pee class=\"sub\">Adoption is where OEE projects die. PerfTrak&#8217;s tablet interface was designed with operators, for operators \u2014 no typing, no menus, no blame. Just &#8220;why did we stop?&#8221; and back to work.<\/pee>\n<div class=\"tab-checks\">\n<div><span class=\"ck\">\u2714<\/span><span><b>Tuned to your plant<\/b> \u2014 learns each line&#8217;s own normal, not a generic model<\/span><\/div>\n<div><span class=\"ck\">\u2714<\/span><span><b>Explainable by design<\/b> \u2014 every alert shows the factors behind it<\/span><\/div>\n<div><span class=\"ck\">\u2714<\/span><span><b>Feeds your tools<\/b> \u2014 alerts to dashboards, email or API<\/span><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div>\n<div class=\"tablet\">\n<div class=\"tab-screen\">\n<div class=\"ts-head\"><span>PerfTrak \u00b7 Machining line 1<\/span><span class=\"st\">STOP \u2014 2 min 14 s<\/span><\/div>\n<div class=\"ts-body\">\n<div class=\"ts-q\">Why did the machine stop?<\/div>\n<div class=\"cause-grid\">\n<div class=\"cause selected\"><span class=\"ic\">\ud83d\udd27<\/span>Tool change<\/div>\n<div class=\"cause\"><span class=\"ic\">\ud83d\udce6<\/span>Material wait<\/div>\n<div class=\"cause\"><span class=\"ic\">\u2699\ufe0f<\/span>Misfeed \/ jam<\/div>\n<div class=\"cause\"><span class=\"ic\">\ud83d\udd04<\/span>Changeover<\/div>\n<div class=\"cause\"><span class=\"ic\">\ud83d\udc64<\/span>No operator<\/div>\n<div class=\"cause\"><span class=\"ic\">\ud83e\uddea<\/span>Quality check<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"ts-foot\"><span>Tap 1 of 2 \u2014 confirm to finish<\/span><span class=\"ok\">Confirm \u2713<\/span><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<div class=\"tap-note\">Explainual operator flow: tap the cause \u2192 tap confirm. Done.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/section>\n<p><!-- INSTALL --><\/p>\n<section id=\"install\">\n<div class=\"wrap\">\n<div style=\"text-align:center;max-width:680px;margin:0 auto\">\n      <span class=\"eyebrow\" style=\"justify-content:center\">Quick &amp; easy<\/span><\/p>\n<h2>Installed in five steps \u2014 without stopping the machine<\/h2>\n<\/p><\/div>\n<div class=\"install-line\">\n<div class=\"inst reveal\">\n<div>\n<h4>Install the module<\/h4>\n<pee>In the electrical cabinet, or outdoors with external boxes<\/pee><\/div>\n<\/div>\n<div class=\"inst reveal\">\n<div>\n<h4>Pick your signal<\/h4>\n<pee>0\u201324V PLC signal, external sensor or OPC UA<\/pee><\/div>\n<\/div>\n<div class=\"inst reveal\">\n<div>\n<h4>Position the tablet<\/h4>\n<pee>At the workstation (or go tablet-free with Light \/ Live)<\/pee><\/div>\n<\/div>\n<div class=\"inst reveal\">\n<div>\n<h4>Configure<\/h4>\n<pee>Products, standard times and your loss-cause tree<\/pee><\/div>\n<\/div>\n<div class=\"inst reveal\">\n<div>\n<h4>Start tracking<\/h4>\n<pee>Production deviations captured live, from minute one<\/pee><\/div>\n<\/div><\/div>\n<div class=\"install-note\">\u23f1 Typical install: <b>under 1 hour per machine<\/b> \u2014 no production stop, no PLC modification, no IT project.<\/div>\n<\/p><\/div>\n<\/section>\n<p><!-- ROI --><\/p>\n<section class=\"roi\" id=\"roi\">\n<div class=\"wrap\">\n<div style=\"text-align:center;max-width:720px;margin:0 auto\">\n      <span class=\"eyebrow\" style=\"justify-content:center\">Make the business case<\/span><\/p>\n<h2>What could early warning save you?<\/h2>\n<pee class=\"sub\" style=\"margin:18px auto 0\">Drag the sliders. Estimate based on a conservative +8 OEE-point gain \u2014 PerfTrak customers average +10 to +15.<\/pee>\n    <\/div>\n<div class=\"roi-box\">\n<div class=\"roi-in\">\n<div class=\"ctrl\">\n          <label>Machines monitored <output id=\"oM\">20<\/output><\/label><br \/>\n          <input type=\"range\" id=\"rM\" min=\"1\" max=\"200\" value=\"20\">\n        <\/div>\n<div class=\"ctrl\">\n          <label>Current average OEE <output id=\"oO\">62%<\/output><\/label><br \/>\n          <input type=\"range\" id=\"rO\" min=\"30\" max=\"90\" value=\"62\">\n        <\/div>\n<div class=\"ctrl\">\n          <label>Cost per machine-hour (USD) <output id=\"oC\">$250<\/output><\/label><br \/>\n          <input type=\"range\" id=\"rC\" min=\"50\" max=\"1000\" step=\"10\" value=\"250\">\n        <\/div>\n<div class=\"ctrl\" style=\"margin-bottom:0\">\n          <label>Production hours \/ year \/ machine <output id=\"oH\">4,000<\/output><\/label><br \/>\n          <input type=\"range\" id=\"rH\" min=\"1000\" max=\"8000\" step=\"100\" value=\"4000\">\n        <\/div>\n<div class=\"roi-note\">Predictable value = machines \u00d7 hours \u00d7 cost \u00d7 8 OEE points. Conservative vs. customer average.<\/div>\n<\/p><\/div>\n<div class=\"roi-out\">\n        <small>Estimated recoverable capacity<\/small><\/p>\n<div class=\"big\" id=\"roiVal\">$1.6M<\/div>\n<pee>per year, by catching drift early<\/pee>\n        <pee style=\"margin-top:6px\">\u2248 <b id=\"roiHrs\" style=\"color:#fff\">6,400<\/b> machine-hours back in production<\/pee>\n        <a class=\"btn btn-red\" href=\"#demo\">Estimate my upside \u2192<\/a>\n      <\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/section>\n<p><!-- VARIANTS --><\/p>\n<section style=\"padding-top:0\">\n<div class=\"wrap\">\n    <span class=\"eyebrow\">One product, three ways to run it<\/span><\/p>\n<h2>Choose your Machine Learning<\/h2>\n<div class=\"var-grid\">\n<div class=\"var-card reveal\">\n        <span class=\"tag\">Standard<\/span><\/p>\n<h4>Perf<b>Trak<\/b><\/h4>\n<pee>Anomaly detection on your full TeepTrak dataset \u2014 drift, micro-stops and quality patterns flagged across every line.<\/pee>\n      <\/div>\n<div class=\"var-card reveal\">\n        <span class=\"tag\">No tablet<\/span><\/p>\n<h4>Perf<b>Trak<\/b> Light<\/h4>\n<pee>Start with one use case \u2014 downtime or quality \u2014 and expand as the model proves its value.<\/pee>\n      <\/div>\n<div class=\"var-card reveal\">\n        <span class=\"tag\">Connected machines<\/span><\/p>\n<h4>Perf<b>Trak<\/b> OPC UA<\/h4>\n<pee>Push predictions into your BI, MES or maintenance system via API \u2014 Machine Learning watches, your systems act.<\/pee>\n      <\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/section>\n<p><!-- RESULTS --><\/p>\n<section class=\"testi\" id=\"results\">\n<div class=\"wrap\">\n<div style=\"text-align:center;max-width:720px;margin:0 auto\">\n      <span class=\"eyebrow\" style=\"justify-content:center\">Customer results<\/span><\/p>\n<h2>The results our customers see every day<\/h2>\n<\/p><\/div>\n<div class=\"bignum\" style=\"margin-top:48px\">\n<div class=\"bn reveal\"><b>42\u219275%<\/b><small>OEE \u2014 Hutchinson<\/small><\/div>\n<div class=\"bn reveal\"><b>~$5M\/yr<\/b><small>recovered \u2014 Stellantis<\/small><\/div>\n<div class=\"bn reveal\"><b>+12 pts<\/b><small>in 6 weeks \u2014 Valeo plants<\/small><\/div>\n<div class=\"bn reveal\"><b>\u20ac230k<\/b><small>annual losses identified<\/small><\/div>\n<\/p><\/div>\n<div class=\"t-grid\">\n<div class=\"t-card reveal\">\n<div class=\"stars\">\u2605\u2605\u2605\u2605\u2605<\/div>\n<pee>&#8220;Quickly adopted by all our production lines thanks to its intuitive interface and clear, real-time dashboards. Operators use it daily for short-interval control.&#8221;<\/pee>\n<div class=\"who\"><b>Alex M.<\/b>Production Manager \u00b7 USA, 51\u2013200 employees<\/div>\n<\/p><\/div>\n<div class=\"t-card reveal\">\n<div class=\"stars\">\u2605\u2605\u2605\u2605\u2605<\/div>\n<pee>&#8220;Real-time OEE tracking and stoppage capture at 3 sites. Fast deployment, operator-friendly interface, clear loss trees, actionable alerts, easy BI exports and APIs.&#8221;<\/pee>\n<div class=\"who\"><b>Laure P.<\/b>Operations \u00b7 Germany, 101\u2013500 employees<\/div>\n<\/p><\/div>\n<div class=\"t-card reveal\">\n<div class=\"stars\">\u2605\u2605\u2605\u2605\u2605<\/div>\n<pee>&#8220;Deployed on all our automated equipment. Strong adoption by operators, elimination of paper and Excel, rapid OEE gains on micro-stops and team organization.&#8221;<\/pee>\n<div class=\"who\"><b>Manuel R.<\/b>Continuous Improvement \u00b7 France, 1,001\u20135,000 employees<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/section>\n<p><!-- INTEGRATIONS --><\/p>\n<section class=\"integ\">\n<div class=\"wrap\">\n    <span class=\"eyebrow\" style=\"justify-content:center\">Plays well with your stack<\/span><\/p>\n<h2>Your data, wherever you need it<\/h2>\n<pee class=\"sub\" style=\"margin:18px auto 0\">Standard APIs and raw-data access. Feed your BI, your ERP, your data lake.<\/pee>\n<div class=\"integ-row\">\n      <span>SAP<\/span><span>Oracle<\/span><span>Power BI<\/span><span>Tableau<\/span><span>Excel export<\/span><span>REST API<\/span><span>OPC UA<\/span>\n    <\/div>\n<\/p><\/div>\n<\/section>\n<p><!-- FAQ --><\/p>\n<section class=\"faq\" id=\"faq\">\n<div class=\"wrap\">\n<div style=\"text-align:center\"><span class=\"eyebrow\" style=\"justify-content:center\">Questions<\/span><\/p>\n<h2>Frequently asked questions<\/h2>\n<\/div>\n<div class=\"faq-list\">\n<div class=\"faq-item open\">\n        <button class=\"faq-q\">Does PerfTrak work on old machines?<\/button><\/p>\n<div class=\"faq-a\">Yes \u2014 100% of machines, whatever their age or make. Non-intrusive sensors or a 0\u201324V PLC signal, with no PLC modification. A machine is typically connected in under 1 hour.<\/div>\n<\/p><\/div>\n<div class=\"faq-item\">\n        <button class=\"faq-q\">Do we need to stop production to install it?<\/button><\/p>\n<div class=\"faq-a\">No. The module installs in the electrical cabinet (or an external box) without stopping the machine, and configuration is done on the platform \u2014 not in your PLC.<\/div>\n<\/p><\/div>\n<div class=\"faq-item\">\n        <button class=\"faq-q\">What if operators don&#8217;t play along?<\/button><\/p>\n<div class=\"faq-a\">The interface asks for exactly two taps, in the operator&#8217;s own vocabulary (your loss tree). Detection is automatic either way \u2014 the operator only qualifies the cause. Customers consistently report adoption from week one; it removes paperwork instead of adding it.<\/div>\n<\/p><\/div>\n<div class=\"faq-item\">\n        <button class=\"faq-q\">How is this different from an MES?<\/button><\/p>\n<div class=\"faq-a\">A traditional MES takes 1\u20132 years and heavy IT resources. PerfTrak deploys in days, focuses specifically on OEE and loss reduction, and delivers ROI in weeks \u2014 and it can feed your MES\/ERP via API if you have one.<\/div>\n<\/p><\/div>\n<div class=\"faq-item\">\n        <button class=\"faq-q\">How quickly do we see results?<\/button><\/p>\n<div class=\"faq-a\">Most plants identify their first major hidden losses within two weeks of the pilot. Valeo reached positive ROI in 6 weeks; Hutchinson grew from 42% to 75% OEE.<\/div>\n<\/p><\/div>\n<div class=\"faq-item\">\n        <button class=\"faq-q\">What does the free 60-day POC include?<\/button><\/p>\n<div class=\"faq-a\">One pilot line, fully equipped \u2014 hardware, platform, onboarding. If we don&#8217;t find at least 10% hidden losses in 60 days, you pay nothing.<\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/p><\/div>\n<\/section>\n<p><!-- FINAL CTA + FORM --><\/p>\n<section class=\"final\" id=\"demo\">\n<div class=\"wrap\">\n<div>\n<h2>See what your data already knows \u2014 on your lines<\/h2>\n<pee class=\"sub\">A 30-minute working session with a TeepTrak engineer. We&#8217;ll map your loss profile and show you PerfTrak running on data like yours.<\/pee>\n<div class=\"guarantee\">\ud83d\udee1 <span><b>Zero-risk POC:<\/b> one pilot line, fully equipped, free for 60 days. If we don&#8217;t find at least 10% hidden losses, you pay nothing.<\/span><\/div>\n<div class=\"trustline\" style=\"margin-top:28px\"><span class=\"stars\">\u2605\u2605\u2605\u2605\u2605<\/span> <span><b style=\"color:#fff\">450+ factories<\/b> \u00b7 30+ countries \u00b7 4.7\/5 on G2 &amp; Capterra<\/span><\/div>\n<\/p><\/div>\n<div class=\"form-card\">\n<h3>Book my demo<\/h3>\n<div class=\"fc-sub\">Or start the free 60-day POC \u2014 mention it in the goals field.<\/div>\n    <div class=\"teeptrak-form-container \">\n        <h3 class=\"teeptrak-form-title\">Request a demo<\/h3>                \n        <form id=\"teeptrak-6a2e2f108579a\" class=\"teeptrak-form\" data-form-type=\"demo_request\">\n            <div style=\"position:absolute;left:-9999px;\"><input type=\"text\" name=\"website_url\" value=\"\" tabindex=\"-1\"><input type=\"text\" name=\"fax_number\" value=\"\" tabindex=\"-1\"><\/div>            \n            <div class=\"teeptrak-form-row teeptrak-form-row-half\">                <div class=\"teeptrak-form-field\">\n                    <label>First name <span class=\"required\">*<\/span><\/label>                    \n                                            <input type=\"text\" name=\"first_name\" required placeholder=\"\">\n                                    <\/div>\n                            <div class=\"teeptrak-form-field\">\n                    <label>Name <span class=\"required\">*<\/span><\/label>                    \n                                            <input type=\"text\" name=\"last_name\" required placeholder=\"\">\n                                    <\/div>\n                            <div class=\"teeptrak-form-field\">\n                    <label>E-mail <span class=\"required\">*<\/span><\/label>                    \n                                            <input type=\"email\" name=\"email\" required placeholder=\"\">\n                                    <\/div>\n                            <div class=\"teeptrak-form-field\">\n                    <label>Phone <span class=\"required\">*<\/span><\/label>                    \n                                            <input type=\"tel\" name=\"phone\" required placeholder=\"\">\n                                    <\/div>\n                            <div class=\"teeptrak-form-field\">\n                    <label>Business <span class=\"required\">*<\/span><\/label>                    \n                                            <input type=\"text\" name=\"company\" required placeholder=\"\">\n                                    <\/div>\n                            <div class=\"teeptrak-form-field\">\n                    <label>Job<\/label>                    \n                                            <input type=\"text\" name=\"job_title\"  placeholder=\"\">\n                                    <\/div>\n            <\/div><div class=\"teeptrak-form-row\">                <div class=\"teeptrak-form-field\">\n                    <label>Goals<\/label>                    \n                                            <textarea name=\"message\" rows=\"3\"  placeholder=\"\"><\/textarea>\n                                    <\/div>\n            <\/div>            \n            <input type=\"hidden\" name=\"page_url\" value=\"https:\/\/teeptrak.com\/en\/machine-learning-anomaly-detection\/\">\n            <input type=\"hidden\" name=\"recaptcha_token\" value=\"\" class=\"teeptrak-recaptcha-token\">\n            \n                        \n            <div class=\"teeptrak-form-row\">\n                <button type=\"submit\" class=\"teeptrak-submit teeptrak-submit-full\">\n                    <span class=\"teeptrak-submit-text\">To book<\/span>\n                    <span class=\"teeptrak-submit-loading\" style=\"display:none;\">Envoi...<\/span>\n                <\/button>\n            <\/div>\n            \n            <div class=\"teeptrak-form-message\" style=\"display:none;\"><\/div>\n        <\/form>\n    <\/div>\n    \n<div class=\"fc-note\" style=\"font-size:12px;color:#999;margin-top:10px;text-align:center\">\ud83d\udd12 Your data is protected under GDPR &amp; 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