{"id":22521,"date":"2026-07-16T13:30:22","date_gmt":"2026-07-16T11:30:22","guid":{"rendered":"https:\/\/www.neuraldesigner.com\/use-cases\/predictive-maintenance\/"},"modified":"2026-08-25T14:03:54","modified_gmt":"2026-08-25T12:03:54","slug":"predictive-maintenance","status":"publish","type":"page","link":"https:\/\/www.neuraldesigner.com\/use-cases\/predictive-maintenance\/","title":{"rendered":"Predictive maintenance using machine learning"},"content":{"rendered":"<style>.ndb{width:100vw;margin-left:calc(50% - 50vw);background:#eeeeee;padding:22px 24px 14px;font-family:\"Outfit\",\"Roboto\",Arial,sans-serif;color:#1b2635}.ndb *{box-sizing:border-box}.ndb a{text-decoration:none}.ndb-wrap{width:min(100%,960px);margin:0 auto}.ndb-lead{font-size:18px;line-height:1.6;color:#3a4a5a;font-weight:300;margin:0 0 22px}.ndb-lead a{color:#2d799f;font-weight:600}.ndb-highlight{margin:0 0 36px;padding:28px 34px;border-radius:18px;background:linear-gradient(135deg,#56a1c8 0%,#245e80 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h3{color:#001233!important;font-size:16px!important;font-weight:600!important;margin:0!important;text-align:center!important;letter-spacing:.03em}body.page-child.parent-pageid-22498 main.site-main .ndb-wrap .ndb-card table td p img{width:52px!important;height:52px!important;max-width:52px!important;min-width:0!important;object-fit:contain!important;margin:0 auto!important;display:inline-block!important}main#content .ndb-card .nd-usecase-title-icon,main#content .ndb-card h3.nd-usecase-icon-title img{display:none!important}main#content .ndb-card h3.nd-usecase-icon-title{display:block!important}.ndb-card .ndb-subhead{color:#001233!important;font-size:19px!important;font-weight:600!important;margin:26px 0 8px!important;text-align:center!important}.ndb-card table:has(td h3) td p:not(:has(img)){font-size:14px!important;line-height:1.5!important;color:#51606f!important;margin:8px auto 0!important;text-align:center!important;max-width:none!important}<\/style><div class=\"ndb\"><div class=\"ndb-wrap\"><div class=\"ndb-lead\"><p>Predictive maintenance determines the actual condition of the equipment and predicts when the company should perform maintenance.<\/p>\n<p>This approach promises cost savings because the company only performs tasks when warranted.<\/p>\n<h3>Contents<\/h3>\n<ol>\n<li><a href=\"#Objectives\">Objectives<\/a>.<\/li>\n<li><a href=\"#Benefits\">Benefits<\/a>.<\/li>\n<li><a href=\"#Approach\">Approach<\/a>.<\/li>\n<li><a href=\"#Conclusions\">Conclusions<\/a>.<\/li>\n<\/ol>\n<\/div><ul class=\"ndb-toc\"><li><a href=\"#objectives\">Objectives<\/a><\/li><li><a href=\"#benefits\">Benefits<\/a><\/li><li><a href=\"#approach\">Approach<\/a><\/li><li><a href=\"#conclusions\">Conclusions<\/a><\/li><\/ul><div class=\"ndb-card\" id=\"objectives\"><h2>Objectives<\/h2><p>Predictive maintenance looks for anomalies, i.e., unexpected measurements that might indicate a problem &#8211; but are not yet so severe that they are a failure.<\/p>\n<p>The challenge is to determine the condition of in-service equipment to predict when the company should perform maintenance and prevent unexpected failures.<\/p><\/p>\n<\/div><div class=\"ndb-card\" id=\"benefits\"><h2>Benefits<\/h2><\/p>\n<p>Predictive maintenance allows for managing problems that could arise in the present and preventing future unexpected events.<\/p>\n<table>\n<tbody>\n<tr>\n<td style=\"text-align: center; border: none;\">\n<p><img decoding=\"async\" style=\"width: 50px;\" src=\"https:\/\/www.neuraldesigner.com\/images\/build.svg\" \/><\/p>\n<h3>IMPROVE PLANNING<\/h3>\n<\/td>\n<td style=\"text-align: center; border: none;\">\n<p><img decoding=\"async\" style=\"width: 50px;\" src=\"https:\/\/www.neuraldesigner.com\/images\/search.svg\" \/><\/p>\n<h3>REDUCE REPAIR COSTS<\/h3>\n<\/td>\n<\/tr>\n<tr>\n<td style=\"text-align: center; border: none;\">\n<p><img decoding=\"async\" style=\"width: 50px;\" src=\"https:\/\/www.neuraldesigner.com\/images\/exclamation.svg\" \/><\/p>\n<h3>REDUCE PRODUCTION LOSSES<\/h3>\n<\/td>\n<td style=\"text-align: center; border: none;\">\n<p><img decoding=\"async\" style=\"width: 50px;\" src=\"https:\/\/www.neuraldesigner.com\/images\/trending_down.svg\" \/><\/p>\n<h3>REDUCE DOWNTIME<\/h3>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div><div class=\"ndb-card\" id=\"approach\"><h2>Approach<\/h2><p>Predictive maintenance is to model equipment failures based on observations of past machine runs and failures.<\/p>\n<p>Neural networks can model the correct operation of the equipment at a given condition and detect when this operation is an anomaly.<\/p>\n<p>That allows early spot potential equipment failures and fix them before they happen.<\/p><\/p>\n<\/div><div class=\"ndb-card ndb-card--accent\" id=\"conclusions\"><h2>Conclusions<\/h2><p>Predictive maintenance saves companies money since they will have shorter downtime and less lost production, better planning of people and materials, and reduced repair costs.<\/p>\n<p><a href=\"https:\/\/www.neuraldesigner.com\/\">Neural Designer<\/a> uses machine learning to build predictive models that represent a broad range of variables associated with the failure of equipment.<\/p>\n<\/div><\/div><\/div>\r\n<!-- nd-index-improvement-v1 --><section class=\"nd-index-improvement\" aria-labelledby=\"nd-predictive-maintenance-practice\"><h2 id=\"nd-predictive-maintenance-practice\">Building a reliable predictive maintenance model<\/h2><p>Begin with time-stamped operating conditions, sensor measurements, maintenance events and a clearly defined outcome. The observation window and prediction horizon must be fixed before training so that future information cannot leak into the model.<\/p><h3>Validation and deployment<\/h3><p>Use chronological validation when equipment behaviour changes over time. Evaluate alert lead time, missed failures and false alarms alongside the usual model metrics, because each has a different operational cost. After deployment, monitor input drift and prediction quality as equipment, processes and maintenance policies change.<\/p><p>Related resources: <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set\/\">prepare the data set<\/a>, <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/testing-analysis\/\">evaluate model performance<\/a> and <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/model-deployment\/\">plan model deployment<\/a>.<\/p><\/section>\r\n","protected":false},"excerpt":{"rendered":"<p>Predictive maintenance determines the actual condition of the equipment and predicts when the company should perform maintenance. This approach promises cost savings because the company only performs tasks when warranted. Contents Objectives. Benefits. Approach. Conclusions. ObjectivesBenefitsApproachConclusionsObjectivesPredictive maintenance looks for anomalies, i.e., unexpected measurements that might indicate a problem &#8211; but are not yet so severe [&hellip;]<\/p>\n","protected":false},"author":152,"featured_media":1677,"parent":22498,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-22521","page","type-page","status-publish","has-post-thumbnail","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Predictive maintenance using machine learning - Neural Designer<\/title>\n<meta name=\"description\" content=\"Explore this Neural Designer use case for Predictive maintenance using machine learning, including problem framing, data, evaluation and limitations.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.neuraldesigner.com\/use-cases\/predictive-maintenance\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Predictive maintenance using machine learning - Neural Designer\" \/>\n<meta property=\"og:description\" content=\"Predictive maintenance determines the actual condition of the equipment and predicts when the company should perform maintenance. 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This approach promises cost savings because the company only performs tasks when warranted. Contents Objectives. Benefits. Approach. Conclusions. ObjectivesBenefitsApproachConclusionsObjectivesPredictive maintenance looks for anomalies, i.e., unexpected measurements that might indicate a problem &#8211; but are not yet so severe [&hellip;]","og_url":"https:\/\/www.neuraldesigner.com\/use-cases\/predictive-maintenance\/","og_site_name":"Neural Designer","article_modified_time":"2026-08-25T12:03:54+00:00","og_image":[{"width":450,"height":235,"url":"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/06\/predictive-maintenance.webp","type":"image\/webp"}],"twitter_card":"summary_large_image","twitter_site":"@NeuralDesigner","twitter_misc":{"Est. reading time":"2 minutes"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/www.neuraldesigner.com\/use-cases\/predictive-maintenance\/","url":"https:\/\/www.neuraldesigner.com\/use-cases\/predictive-maintenance\/","name":"Predictive maintenance using machine learning - Neural Designer","isPartOf":{"@id":"https:\/\/www.neuraldesigner.com\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.neuraldesigner.com\/use-cases\/predictive-maintenance\/#primaryimage"},"image":{"@id":"https:\/\/www.neuraldesigner.com\/use-cases\/predictive-maintenance\/#primaryimage"},"thumbnailUrl":"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/06\/predictive-maintenance.webp","datePublished":"2026-07-16T11:30:22+00:00","dateModified":"2026-08-25T12:03:54+00:00","breadcrumb":{"@id":"https:\/\/www.neuraldesigner.com\/use-cases\/predictive-maintenance\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.neuraldesigner.com\/use-cases\/predictive-maintenance\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.neuraldesigner.com\/use-cases\/predictive-maintenance\/#primaryimage","url":"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/06\/predictive-maintenance.webp","contentUrl":"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/06\/predictive-maintenance.webp","width":450,"height":235},{"@type":"BreadcrumbList","@id":"https:\/\/www.neuraldesigner.com\/use-cases\/predictive-maintenance\/#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/www.neuraldesigner.com\/"},{"@type":"ListItem","position":2,"name":"Neural Designer Use Cases","item":"https:\/\/www.neuraldesigner.com\/use-cases\/"},{"@type":"ListItem","position":3,"name":"Predictive maintenance using machine learning"}]},{"@type":"WebSite","@id":"https:\/\/www.neuraldesigner.com\/#website","url":"https:\/\/www.neuraldesigner.com\/","name":"Neural Designer","description":"Explainable AI Platform","publisher":{"@id":"https:\/\/www.neuraldesigner.com\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.neuraldesigner.com\/?s={search_term_string}"},"query-input":{"@type":"PropertyValueSpecification","valueRequired":true,"valueName":"search_term_string"}}],"inLanguage":"en-US"},{"@type":"Organization","@id":"https:\/\/www.neuraldesigner.com\/#organization","name":"Neural Designer","url":"https:\/\/www.neuraldesigner.com\/","logo":{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.neuraldesigner.com\/#\/schema\/logo\/image\/","url":"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/05\/logo-neural-1.png","contentUrl":"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/05\/logo-neural-1.png","width":1024,"height":223,"caption":"Neural Designer"},"image":{"@id":"https:\/\/www.neuraldesigner.com\/#\/schema\/logo\/image\/"},"sameAs":["https:\/\/x.com\/NeuralDesigner","https:\/\/es.linkedin.com\/showcase\/neuraldesigner\/"]}]}},"_links":{"self":[{"href":"https:\/\/www.neuraldesigner.com\/api\/wp\/v2\/pages\/22521","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.neuraldesigner.com\/api\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.neuraldesigner.com\/api\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.neuraldesigner.com\/api\/wp\/v2\/users\/152"}],"replies":[{"embeddable":true,"href":"https:\/\/www.neuraldesigner.com\/api\/wp\/v2\/comments?post=22521"}],"version-history":[{"count":3,"href":"https:\/\/www.neuraldesigner.com\/api\/wp\/v2\/pages\/22521\/revisions"}],"predecessor-version":[{"id":23704,"href":"https:\/\/www.neuraldesigner.com\/api\/wp\/v2\/pages\/22521\/revisions\/23704"}],"up":[{"embeddable":true,"href":"https:\/\/www.neuraldesigner.com\/api\/wp\/v2\/pages\/22498"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.neuraldesigner.com\/api\/wp\/v2\/media\/1677"}],"wp:attachment":[{"href":"https:\/\/www.neuraldesigner.com\/api\/wp\/v2\/media?parent=22521"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}