{"id":22514,"date":"2026-07-16T13:30:10","date_gmt":"2026-07-16T11:30:10","guid":{"rendered":"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/"},"modified":"2026-08-28T11:24:37","modified_gmt":"2026-08-28T09:24:37","slug":"quality-improvement","status":"publish","type":"page","link":"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/","title":{"rendered":"Product quality improvement using machine learning"},"content":{"rendered":"<style>\n.nd-math-block {\n  display: block;\n  max-width: 100%;\n  overflow-x: auto;\n  margin: 1rem 0;\n  padding: 0.45rem 0;\n  text-align: center;\n}\n.nd-math-block math {\n  font-size: 1.04em;\n}\n<\/style>\n<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 100%);color:#fff;box-shadow:0 16px 34px rgba(30,83,116,.22)}.ndb-highlight p{margin:0;color:#fff;font-size:20px;line-height:1.5;font-weight:400}.ndb-highlight b{font-weight:800}.ndb-toc{list-style:none;display:flex;flex-wrap:wrap;gap:10px;justify-content:center;margin:0 0 42px;padding:0}.ndb-toc a{padding:10px 18px;background:#f2f2f2;border-radius:22px;color:#12354b!important;font-size:14px;font-weight:600;box-shadow:-6px -6px 12px rgba(255,255,255,.9),6px 6px 12px rgba(30,83,116,.10)}.ndb-toc a:hover{color:#2d799f!important}.ndb-card{margin:0 0 26px;padding:32px 40px;background:#f5f6f7;border-radius:20px;box-shadow:-12px -12px 24px rgba(255,255,255,.9),12px 12px 24px rgba(30,83,116,.10);scroll-margin-top:90px}.ndb-card h2{margin:0 0 20px;padding-bottom:12px;color:#001233;font-size:24px;font-weight:700;position:relative;border-bottom:1px solid #dbe5ec}.ndb-card h2:after{content:\"\";position:absolute;left:0;bottom:-1px;width:62px;height:3px;background:#56a1c8;border-radius:2px}.ndb-card p{margin:0 0 14px;font-size:16.5px;line-height:1.62;color:#33424f}.ndb-card a{color:#2d799f;font-weight:500}.ndb-card ul{margin:0 0 14px;padding-left:22px}.ndb-card li{margin:5px 0;font-size:16px;line-height:1.5;color:#33424f}.ndb-card img:not([src$=\".svg\"]):not([data-src$=\".svg\"]){display:block;width:auto;max-width:min(560px,100%);height:auto;margin:22px auto;border-radius:12px;box-shadow:0 12px 28px rgba(0,18,51,.12)}.ndb-card th img[src$=\".svg\"],.ndb-card th img[data-src$=\".svg\"],.ndb-card img[src$=\".svg\"],.ndb-card img[data-src$=\".svg\"]{display:inline-block;max-width:24px;height:auto;margin:0 6px -4px 0;box-shadow:none}.ndb-card table{border-collapse:separate;border-spacing:0;width:100%;max-width:100%;margin:22px 0;font-size:15px;background:#fbfcfd;border-radius:12px;overflow:hidden;box-shadow:0 10px 24px rgba(0,18,51,.08)}.ndb-card th,.ndb-card td{padding:11px 16px;border-bottom:1px solid #e6ecf0;text-align:left;vertical-align:top}.ndb-card thead th{background:#12354b;color:#fff;font-weight:600;text-align:center}.ndb-card tbody th{background:#e9f1f6;color:#12354b;font-weight:600}.ndb-card td{color:#33424f}.ndb-card table ul{margin:0;padding-left:18px}.ndb-card table li{font-size:14px}.ndb-card pre{margin:22px 0;padding:22px 24px;background:#0b1830!important;color:#e6eef5!important;border-radius:14px;overflow-x:auto;font-family:Consolas,Menlo,monospace;font-size:12.5px;line-height:1.5;white-space:pre}.ndb-card--accent{background:#e9f2f8}@media(max-width:820px){.ndb-card{padding:26px 22px}.ndb-card h2{font-size:21px}.ndb-toc{gap:8px}}@media(max-width:640px){.ndb{padding:12px 14px}}.ndb-card thead th{background:#12354b!important;color:#fff!important}.ndb-card tbody th{background:#e9f1f6!important;color:#12354b!important}.ndb-card td{background:#fbfcfd!important;color:#33424f!important}.ndb-card .mjx-chtml.MJXc-display{overflow-x:auto;overflow-y:hidden;max-width:100%;padding:2px 0 8px}.ndb-card .mjx-chtml.MathJax_CHTML{font-size:18px!important}.ndb-card img,.ndb-lead img{display:block!important;width:auto!important;max-width:min(560px,100%)!important;height:auto!important;margin:22px auto!important;border-radius:12px!important;box-shadow:0 12px 28px rgba(0,18,51,.12)!important}.ndb-card .nd-benefit-icon{margin:0 auto 8px!important;text-align:center!important}.ndb-card .nd-benefit-icon svg{width:56px!important;height:56px!important;color:#2d799f!important}.ndb-card table:has(.nd-benefit-icon),.ndb-card table:has(svg){background:transparent!important;box-shadow:none!important;border-radius:0!important}.ndb-card table:has(.nd-benefit-icon) td,.ndb-card table:has(svg) td{background:transparent!important;border:0!important;text-align:center!important;vertical-align:top!important;padding:16px 20px!important}.ndb-card table:has(svg) th{background:transparent!important;border:0!important}.ndb-card table td svg,.ndb-card p>svg{width:56px!important;height:56px!important;max-width:56px!important;color:#2d799f!important}.ndb-card table h3{color:#001233!important;font-size:18px!important;font-weight:600!important;margin:6px 0 0!important;text-align:center!important}.ndb .ndb-card img{max-width:min(560px,100%)!important;width:auto!important;height:auto!important}.ndb .ndb-card .nd-usecase-icon-source{text-align:center!important;margin:0 auto!important}.ndb .ndb-card .nd-usecase-icon-source img,.ndb .ndb-card .nd-usecase-icon-source svg,.ndb .ndb-card td img[src*=\".svg\"],.ndb .ndb-card td svg{width:60px!important;height:60px!important;max-width:60px!important;margin:0 auto 6px!important;display:inline-block!important;box-shadow:none!important;border-radius:0!important;color:#2d799f!important}body.page-child.parent-pageid-22498 main.site-main .ndb-wrap .ndb-card img{max-width:min(560px,100%)!important;width:auto!important;height:auto!important;display:block!important;margin:22px auto!important}body.page-child.parent-pageid-22498 main.site-main .ndb-wrap .ndb-lead img{max-width:min(540px,100%)!important;width:auto!important;height:auto!important;display:block!important;margin:20px auto!important}body.page-child.parent-pageid-22498 main.site-main .ndb-wrap .nd-usecase-icon-source img,body.page-child.parent-pageid-22498 main.site-main .ndb-wrap .ndb-card td img[src*=\".svg\"],body.page-child.parent-pageid-22498 main.site-main .ndb-wrap .ndb-card td svg,body.page-child.parent-pageid-22498 main.site-main .ndb-wrap .nd-benefit-icon svg{width:60px!important;height:60px!important;max-width:60px!important;display:inline-block!important;margin:0 auto 6px!important;color:#2d799f!important;box-shadow:none!important;border-radius:0!important}.ndb-card p:has(>img),.ndb-card figure,.ndb-lead p:has(>img),.ndb-lead figure{max-width:560px!important;margin-left:auto!important;margin-right:auto!important;text-align:center!important}.ndb-card p:has(>.nd-usecase-icon-source),.ndb-card .nd-usecase-icon-source{max-width:none!important}.ndb-card table:has(td h3){background:transparent!important;box-shadow:none!important;border:0!important;width:100%!important;table-layout:fixed!important;margin:14px 0!important}.ndb-card table:has(td h3) td{background:transparent!important;border:0!important;text-align:center!important;vertical-align:top!important;padding:16px 14px!important}.ndb-card table:has(td h3) td p{margin:0 0 12px!important;text-align:center!important;max-width:none!important}.ndb-card table:has(td h3) td p img{display:inline-block!important;width:52px!important;height:52px!important;max-width:52px!important;object-fit:contain!important;margin:0 auto!important;box-shadow:none!important;border-radius:0!important}.ndb-card table:has(td h3) td 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>Quality improvement investigates the relationship between the features of a product and how well it complies with or conforms to its design.<\/p><p>This article explains how machine learning and <a href=\"https:\/\/www.neuraldesigner.com\/\">Neural Designer<\/a> can be used to model engineering systems and optimize industrial processes.<\/p><p>This approach can be explored with Neural Designer.<\/p><\/div><ul class=\"ndb-toc\"><li><a href=\"#data-set\">Data set<\/a><\/li><li><a href=\"#mathematical-model\">Mathematical model<\/a><\/li><li><a href=\"#response-optimization\">Response optimization<\/a><\/li><li><a href=\"#conclusions\">Conclusions<\/a><\/li><\/ul><div class=\"ndb-card\" id=\"data-set\"><h2>Data set<\/h2><p>The quality index can be objective (a physical or chemical test) or subjective (the evaluation by a person). The <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set\/\">data set<\/a> contains measurements of our product.<\/p><p>It comprises the design and quality <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set\/#Variables\">variables<\/a>.<\/p><p><b>Design variables<\/b> are those <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set\/#InputVariables\">inputs<\/a> that determine the quality of the product. Some examples are:<\/p><ul><li>Proportions of product components.<\/li><li>Physical or chemical measures of the product.<\/li><li>Etc.<\/li><\/ul><p><b>Quality variables<\/b> are the <a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/data-set\/#TargetVariables\">outputs<\/a> of the product and depend on the design variables.<\/p><p>Product quality optimization can consider different targets:<\/p><table><tbody><tr><td style=\"text-align:center;border:none;\"><p><img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/icon-device-hub.svg\" width=\"52\" height=\"52\" \/><\/p><h3>PRODUCT FEATURES<\/h3><\/td><td style=\"text-align:center;border:none;\"><p><img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/icon-thumbs.svg\" width=\"52\" height=\"52\" \/><\/p><h3>HUMAN PREFERENCES<\/h3><\/td><\/tr><\/tbody><\/table><p>Usually, we will have a single quality variable, although there may be several.<\/p><\/div><div class=\"ndb-card\" id=\"mathematical-model\"><h2>Mathematical model<\/h2><p>The model of the quality of a product is a mathematical description that adequately predicts the quality of the product from the design variables.<\/p>\n<p>More specifically, it relates the quality variables with the design variables.<\/p>\n<p><span class=\"nd-math-block\"><math xmlns=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" display=\"block\"><semantics><mrow><mtext>quality_variables<\/mtext><mo>=<\/mo><mtext>function<\/mtext><mo stretchy=\"false\">(<\/mo><mtext>design_variables<\/mtext><mo stretchy=\"false\">)<\/mo><\/mrow><annotation encoding=\"application\/x-tex\">quality_variables = function(design_variables)<\/annotation><\/semantics><\/math><\/span><\/p>\n<p><a href=\"https:\/\/www.neuraldesigner.com\/learning\/tutorials\/neural-network\/\">Neural networks<\/a>\u00a0are algorithms used to fit multi-dimensional and non-linear functions from data sets.<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/performance-optimization-neural-network.webp\" \/><\/p>\n<p>The inputs to the neural network include the design variables.<br \/>\nThe outputs from the neural network are the predicted quality of the product.<\/p>\n<\/div><div class=\"ndb-card\" id=\"response-optimization\"><h2>Response optimization<\/h2><p>The objective of the response optimization algorithm is to exploit the mathematical model to look for optimal design variables.<\/p>\n<p>Indeed, the predictive model allows us to simulate different possible products and adjust the design variables to improve quality.<\/p>\n<p>More specifically, product quality optimization can be formulated as follows:<\/p>\n<p style=\"border: 1px solid; text-align: center;\"><b><br \/>\nDetermine the design variables that maximize the quality variables.<br \/>\n<\/b><\/p>\n<p>The next figure illustrates the response optimization process.<\/p>\n<p><img decoding=\"async\" src=\"https:\/\/www.neuraldesigner.com\/images\/response-optimization.svg\" \/><\/p>\n<p>As we can see, the design values, <b>(x1*,x2*)<\/b>, maximize the quality value.<\/p>\n<p>A quality optimization problem might also be specified by a set of constraints on the product&#8217;s inputs and outputs.<\/p>\n<p>An example is to maximize the compressive strength of concrete while maintaining the amount of cement at the desired value.<\/p>\n<\/div><div class=\"ndb-card ndb-card--accent\" id=\"conclusions\"><h2>Conclusions<\/h2><p>Machine learning can predict the quality of a product based on its design.<\/p>\n<p>That allows us to simulate different products and adjust the design to improve quality.<\/p>\n<p>Some examples are to\u00a0<a href=\"https:\/\/www.neuraldesigner.com\/learning\/examples\/wine-quality-improvement\/\">model wine preferences from physicochemical properties<\/a>\u00a0or to\u00a0<a href=\"https:\/\/www.neuraldesigner.com\/learning\/examples\/concrete-properties-assesment\/\">model the compressive strength of high performance concretes<\/a>.<\/p>\n<p><a href=\"https:\/\/www.neuraldesigner.com\/downloads\/\">Neural Designer<\/a> uses neural networks to model the quality of products.<br \/>\nIt also contains response optimization algorithms to fine-tune the design variables and optimize quality.<\/p>\n<\/div><\/div><\/div>","protected":false},"excerpt":{"rendered":"<p>Quality improvement investigates the relationship between the features of a product and how well it complies with or conforms to its design.This article explains how machine learning and Neural Designer can be used to model engineering systems and optimize industrial processes.This approach can be explored with Neural Designer.Data setMathematical modelResponse optimizationConclusionsData setThe quality index can [&hellip;]<\/p>\n","protected":false},"author":152,"featured_media":1653,"parent":22498,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-22514","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>Product quality improvement using machine learning - Neural Designer<\/title>\n<meta name=\"description\" content=\"Explore this Neural Designer use case for Product quality improvement 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\/quality-improvement\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Product quality improvement using machine learning - Neural Designer\" \/>\n<meta property=\"og:description\" content=\"Quality improvement investigates the relationship between the features of a product and how well it complies with or conforms to its design.This article explains how machine learning and Neural Designer can be used to model engineering systems and optimize industrial processes.This approach can be explored with Neural Designer.Data setMathematical modelResponse optimizationConclusionsData setThe quality index can [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/\" \/>\n<meta property=\"og:site_name\" content=\"Neural Designer\" \/>\n<meta property=\"article:modified_time\" content=\"2026-08-28T09:24:37+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/06\/quality-improvement.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"628\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/webp\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:site\" content=\"@NeuralDesigner\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/\",\"url\":\"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/\",\"name\":\"Product quality improvement using machine learning - Neural Designer\",\"isPartOf\":{\"@id\":\"https:\/\/www.neuraldesigner.com\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/#primaryimage\"},\"image\":{\"@id\":\"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/06\/quality-improvement.webp\",\"datePublished\":\"2026-07-16T11:30:10+00:00\",\"dateModified\":\"2026-08-28T09:24:37+00:00\",\"breadcrumb\":{\"@id\":\"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"en-US\",\"@id\":\"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/#primaryimage\",\"url\":\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/06\/quality-improvement.webp\",\"contentUrl\":\"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/06\/quality-improvement.webp\",\"width\":1200,\"height\":628},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/#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\":\"Product quality improvement 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\/\"]}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Product quality improvement using machine learning - Neural Designer","description":"Explore this Neural Designer use case for Product quality improvement using machine learning, including problem framing, data, evaluation and limitations.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/","og_locale":"en_US","og_type":"article","og_title":"Product quality improvement using machine learning - Neural Designer","og_description":"Quality improvement investigates the relationship between the features of a product and how well it complies with or conforms to its design.This article explains how machine learning and Neural Designer can be used to model engineering systems and optimize industrial processes.This approach can be explored with Neural Designer.Data setMathematical modelResponse optimizationConclusionsData setThe quality index can [&hellip;]","og_url":"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/","og_site_name":"Neural Designer","article_modified_time":"2026-08-28T09:24:37+00:00","og_image":[{"width":1200,"height":628,"url":"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/06\/quality-improvement.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\/quality-improvement\/","url":"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/","name":"Product quality improvement using machine learning - Neural Designer","isPartOf":{"@id":"https:\/\/www.neuraldesigner.com\/#website"},"primaryImageOfPage":{"@id":"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/#primaryimage"},"image":{"@id":"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/#primaryimage"},"thumbnailUrl":"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/06\/quality-improvement.webp","datePublished":"2026-07-16T11:30:10+00:00","dateModified":"2026-08-28T09:24:37+00:00","breadcrumb":{"@id":"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/#breadcrumb"},"inLanguage":"en-US","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/"]}]},{"@type":"ImageObject","inLanguage":"en-US","@id":"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/#primaryimage","url":"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/06\/quality-improvement.webp","contentUrl":"https:\/\/www.neuraldesigner.com\/wp-content\/uploads\/2023\/06\/quality-improvement.webp","width":1200,"height":628},{"@type":"BreadcrumbList","@id":"https:\/\/www.neuraldesigner.com\/use-cases\/quality-improvement\/#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":"Product quality improvement 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\/22514","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=22514"}],"version-history":[{"count":7,"href":"https:\/\/www.neuraldesigner.com\/api\/wp\/v2\/pages\/22514\/revisions"}],"predecessor-version":[{"id":23831,"href":"https:\/\/www.neuraldesigner.com\/api\/wp\/v2\/pages\/22514\/revisions\/23831"}],"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\/1653"}],"wp:attachment":[{"href":"https:\/\/www.neuraldesigner.com\/api\/wp\/v2\/media?parent=22514"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}