{"id":31858,"date":"2026-04-15T10:00:00","date_gmt":"2026-04-15T09:00:00","guid":{"rendered":"https:\/\/www.engineernewsnetwork.com\/blog\/?p=31858"},"modified":"2026-04-14T10:34:45","modified_gmt":"2026-04-14T09:34:45","slug":"metal-additive-manufacturing-from-spreadsheet-survival-to-digital-quality-backbone","status":"publish","type":"post","link":"https:\/\/www.engineernewsnetwork.com\/blog\/metal-additive-manufacturing-from-spreadsheet-survival-to-digital-quality-backbone\/","title":{"rendered":"Metal additive manufacturing: from spreadsheet survival to digital quality backbone"},"content":{"rendered":"\n<p><strong>Tim\u00a0Wischeropp makes the point that\u00a0additive manufacturing (AM) has earned its place in production. Now it needs the quality infrastructure to match. Not more complexity. Not more dashboards. A backbone. A discipline. A simpler, more industrial way of proving\u00a0(and improving)\u00a0quality<\/strong><\/p>\n\n\n\n<p>Metal additive manufacturing has crossed an important threshold. It is no longer &#8216;promising&#8217;. It is working. Real parts. Real supply chains. Real responsibility.\u00a0<\/p>\n\n\n\n<p>And yet, in far too many production environments, the way we prove quality still looks like an early-stage experiment. Not because engineers are careless, but&nbsp;because&nbsp;they\u2019re&nbsp;doing heroic work with tools that were never designed for industrial AM.&nbsp;<\/p>\n\n\n\n<p>The best engineers I meet are not short on knowledge.\u00a0They are\u00a0short on time.\u00a0They are\u00a0trapped in a loop of manual documentation, spreadsheet archaeology, and post-mortem investigations. When a part fails, the first question\u00a0is not\u00a0&#8216;why did it happen?&#8217;\u00a0It is\u00a0&#8216;where is the data?&#8217;.\u00a0<\/p>\n\n\n\n<p>This is not a small inconvenience. It is one of the main reasons AM still struggles to scale smoothly into serial production.&nbsp;<\/p>\n\n\n\n<p><strong>The quality myth AM needs to drop<\/strong>\u00a0<\/p>\n\n\n\n<p>There is\u00a0a myth that keeps resurfacing in AM.\u00a0If we add enough sensors, quality becomes automatic.\u00a0It is\u00a0an attractive\u00a0idea. In-situ monitoring, AI, digital twins,\u00a0all powerful concepts. But they\u00a0do not\u00a0solve the core production problem on their own\u00a0which is\u00a0reproducibility.\u00a0Reproducibility\u00a0is not a dashboard.\u00a0It is\u00a0a system.\u00a0<\/p>\n\n\n\n<p>In mature industries, quality management is not a &#8216;project&#8217;.\u00a0It is\u00a0infrastructure. It lives in the way data is captured, linked, controlled, analysed, and turned into decisions. AM will not become a dependable production technology by collecting more data. It will become dependable by making the right data usable,\u00a0and by embedding disciplines like SPC into daily work.\u00a0<\/p>\n\n\n\n<p><strong>Excel is not the enemy\u00a0&#8211;\u00a0it is the warning light<\/strong>\u00a0<\/p>\n\n\n\n<p>Let us\u00a0be fair,\u00a0Excel has been one of AM\u2019s most important accelerators. It let teams move fast when software ecosystems were immature.\u00a0The problem begins when Excel becomes the backbone.\u00a0Spreadsheets are great for analysis, but they are terrible for relationships:\u00a0<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>this powder batch to that build job,\u00a0<\/li>\n\n\n\n<li>this parameter set to that inspection trend,\u00a0<\/li>\n\n\n\n<li>this post-processing route to that failure mode.\u00a0<\/li>\n<\/ul>\n\n\n\n<p>Those relationships are the heart of AM quality,\u00a0and they simply\u00a0do not\u00a0survive scale when they live in human convention rather than a structured system.\u00a0So,\u00a0when I see a factory using spreadsheets to prove quality, I\u00a0do not\u00a0see incompetence. I see a signal: the operation has outgrown its information infrastructure.\u00a0<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><a href=\"https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2026\/04\/image-2.png\"><img loading=\"lazy\" decoding=\"async\" width=\"601\" height=\"394\" src=\"https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2026\/04\/image-2.png\" alt=\"\" class=\"wp-image-31861\" srcset=\"https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2026\/04\/image-2.png 601w, https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2026\/04\/image-2-300x197.png 300w\" sizes=\"auto, (max-width: 601px) 100vw, 601px\" \/><\/a><figcaption class=\"wp-element-caption\"><em>Build job file in\u00a0amsight\u00a0\u2013 connecting data from powder to final part<\/em><\/figcaption><\/figure>\n<\/div>\n\n\n<p>Monitoring is not quality management<\/p>\n\n\n\n<p>Another pattern I see repeatedly&nbsp;is&nbsp;organisations investing&nbsp;in&nbsp;process&nbsp;monitoring&nbsp;systems, then expecting&nbsp;monitoring to become quality management.&nbsp;Monitoring can be valuable. It can alert you to anomalies. It can support development. It can provide&nbsp;additional&nbsp;signals for process understanding.&nbsp;But&nbsp;monitoring&nbsp;alone does not give you:&nbsp;<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>a controlled, auditable data model across powder \u2192 process \u2192 inspection,\u00a0<\/li>\n\n\n\n<li>stability evidence over time,\u00a0<\/li>\n\n\n\n<li>repeatable reporting for customers and auditors,\u00a0<\/li>\n\n\n\n<li>or rapid root-cause analysis anchored in the full process chain.\u00a0<\/li>\n<\/ul>\n\n\n\n<p>In other words, monitoring can tell\u00a0you\u00a0&#8216;something\u00a0happened&#8217;. Quality management tells\u00a0you\u00a0&#8216;it\u00a0matters, here is why, and here is what we do next.&#8217;<\/p>\n\n\n\n<p>If you use monitoring as your quality system, you often end up with the worst of both worlds, huge data volumes and still no consistent,&nbsp;queryable&nbsp;story of the part.&nbsp;<\/p>\n\n\n\n<p><strong>Make AM simpler with SPC<\/strong>\u00a0<\/p>\n\n\n\n<p>If there is one discipline AM needs to embrace more aggressively in production, it is Statistical Process Control (SPC).\u00a0SPC is not glamorous, and that is\u00a0kind of the\u00a0point.\u00a0It is\u00a0how mature manufacturing stops reacting to defects and starts controlling variation.\u00a0It is\u00a0how you detect drift early, quantify stability, and improve processes based on evidence\u00a0(not intuition and emergency meetings).\u00a0<\/p>\n\n\n\n<p>In AM, SPC becomes powerful when the data\u00a0is not\u00a0trapped in silos. When powder lots, builds, machine events, post-processing\u00a0steps\u00a0and inspection results are connected at part level, SPC stops being a quarterly analytics exercise and becomes a daily operating rhythm.\u00a0<\/p>\n\n\n\n<p>This is the future\u00a0I am\u00a0evangelical about,\u00a0AM that feels less like a research lab and more like a reliable production line,\u00a0not because we reduced complexity in the physics, but because we reduced complexity in how we manage evidence.\u00a0<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><a href=\"https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2026\/04\/image.png\"><img loading=\"lazy\" decoding=\"async\" width=\"601\" height=\"404\" src=\"https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2026\/04\/image.png\" alt=\"\" class=\"wp-image-31859\" srcset=\"https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2026\/04\/image.png 601w, https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2026\/04\/image-300x202.png 300w, https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2026\/04\/image-110x75.png 110w\" sizes=\"auto, (max-width: 601px) 100vw, 601px\" \/><\/a><figcaption class=\"wp-element-caption\"><em>Analysing trends and shifts with SPC module in\u00a0amsight<\/em><\/figcaption><\/figure>\n<\/div>\n\n\n<p><strong>Why AM needs a digital quality backbone<\/strong>\u00a0<\/p>\n\n\n\n<p>In&nbsp;amsight&nbsp;we use a phrase that captures the shift,&nbsp;digital quality backbone.&nbsp;<\/p>\n\n\n\n<p>What we mean is simple. Production-level quality software that connects powder, process, and inspection data into one structured, reusable asset,&nbsp;so traceability, compliance reporting, SPC, and root-cause analysis stop being manual heroics.&nbsp;<\/p>\n\n\n\n<p>Through\u00a0our Production Monitoring, we\u00a0facilitate\u00a0the practical outcome: &#8216;catch problems before they become scrap&#8217;, with live KPIs, built-in SPC, and root-cause analysis in minutes.\u00a0\u00a0<br>On Reports &amp; Analytics, the message is equally pragmatic: stop rebuilding reports from scratch; define templates once and generate them anytime, with analytics built in.\u00a0\u00a0<\/p>\n\n\n\n<p>This&nbsp;isn\u2019t&nbsp;about replacing ERP or MES.&nbsp;It\u2019s&nbsp;about doing one thing exceptionally well,&nbsp;owning the production-level quality data model for AM&nbsp;so the rest of the stack can breathe.&nbsp;<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"aligncenter size-full\"><a href=\"https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2026\/04\/image-1.png\"><img loading=\"lazy\" decoding=\"async\" width=\"601\" height=\"338\" src=\"https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2026\/04\/image-1.png\" alt=\"\" class=\"wp-image-31860\" srcset=\"https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2026\/04\/image-1.png 601w, https:\/\/www.engineernewsnetwork.com\/blog\/wp-content\/uploads\/2026\/04\/image-1-300x169.png 300w\" sizes=\"auto, (max-width: 601px) 100vw, 601px\" \/><\/a><figcaption class=\"wp-element-caption\"><em>Overview of typical software-stack for\u00a0AM production, including\u00a0amsight\u00a0as\u00a0production-level QM software<\/em><\/figcaption><\/figure>\n<\/div>\n\n\n<p><strong>The strategic advantage most people miss<\/strong><\/p>\n\n\n\n<p>Here is\u00a0the non-obvious point. A\u00a0quality backbone\u00a0is not\u00a0only about compliance,\u00a0it is\u00a0about competitiveness.\u00a0When your AM quality data is structured:\u00a0<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>audits become faster and less disruptive,\u00a0<\/li>\n\n\n\n<li>scrap reduction becomes systematic, not accidental,\u00a0<\/li>\n\n\n\n<li>qualification moves from a painful ritual to a repeatable process,\u00a0<\/li>\n\n\n\n<li>and scaling from five machines to 50 becomes a matter of expanding a system, not expanding chaos.\u00a0<\/li>\n<\/ul>\n\n\n\n<p>In high-stakes sectors\u00a0(space, aerospace, medical, semiconductor supply chains)\u00a0this is the difference between &#8216;AM is interesting&#8217; and &#8216;AM is dependable&#8217;.\u00a0And dependability is what unlocks volume.\u00a0<\/p>\n\n\n\n<p><strong>Start small, but start properly<\/strong>\u00a0<\/p>\n\n\n\n<p>The mistake some organisations make is treating &#8216;digital quality&#8217; as a multi-year transformation. It\u00a0does npt\u00a0have to be.\u00a0A sensible approach is:\u00a0<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Choose one product family or machine cluster.\u00a0<\/li>\n\n\n\n<li>Connect the essential data sources (powder, build, post-process, inspection).\u00a0<\/li>\n\n\n\n<li>Automate the boring pain first\u00a0(documentation, standard reports, traceability).\u00a0<\/li>\n\n\n\n<li>Add SPC and drift detection.\u00a0<\/li>\n\n\n\n<li>Use real wins\u00a0(fewer hours, fewer surprises, fewer scrapped builds)\u00a0to justify scaling.\u00a0<\/li>\n<\/ol>\n\n\n\n<p>The goal is not digital for digital\u2019s sake. The goal is\u00a0production confidence.\u00a0<\/p>\n\n\n\n<p><strong>Summary<\/strong><\/p>\n\n\n\n<p>If you take one provocation from this article, let it be this.\u00a0If your AM quality story is still assembled in spreadsheets, you\u00a0do not\u00a0have a quality system,\u00a0you have a coping mechanism.\u00a0<\/p>\n\n\n\n<p>That\u2019s\u00a0not a criticism.\u00a0It is\u00a0a call to maturity.\u00a0<\/p>\n\n\n\n<p>AM has earned its place in production. Now it needs the quality infrastructure to match. Not more complexity. Not more dashboards. A backbone. A discipline. A simpler, more industrial way of proving&nbsp;(and improving)&nbsp;quality.&nbsp;<\/p>\n\n\n\n<p>And\u00a0that is\u00a0the shift\u00a0we\u2019re\u00a0committed to driving.\u00a0<\/p>\n\n\n\n<p>The software covers the entire AM production chain\u00a0&#8211;\u00a0from\u00a0powder\u00a0to final part\u00a0&#8211;\u00a0enabling reproducibility, traceability, statistical process control, and efficient root-cause analysis.\u00a0amsight\u00a0supports manufacturers and AM service providers in meeting the stringent quality and documentation requirements of regulated industries such as space, aviation,\u00a0defense, and medical technology.\u00a0<\/p>\n\n\n\n<p>Tim\u00a0Wischeropp is CEO &amp; Co-Founder,\u00a0<strong><a href=\"http:\/\/www.amsight.de\" type=\"link\" id=\"www.amsight.de\">amsight<\/a><\/strong>.\u00a0amsight\u00a0develops software for data-driven quality assurance and analytics in industrial additive manufacturing.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tim\u00a0Wischeropp makes the point that\u00a0additive manufacturing (AM) has earned its place in production. Now it needs the quality infrastructure to match. Not more complexity. Not more dashboards. A backbone. A discipline. A simpler, more industrial way of proving\u00a0(and improving)\u00a0quality Metal additive manufacturing has crossed an important threshold. It is no longer &#8216;promising&#8217;. It is working. &hellip;<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[199],"tags":[14708,6698,14709],"class_list":["post-31858","post","type-post","status-publish","format-standard","","category-news-views-and-opinion","tag-amsight","tag-metal-additive-manufacturing","tag-statistical-process-control-spc"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Metal additive manufacturing: from spreadsheet survival to digital quality backbone - Engineer News Network<\/title>\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.engineernewsnetwork.com\/blog\/metal-additive-manufacturing-from-spreadsheet-survival-to-digital-quality-backbone\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Metal additive manufacturing: from spreadsheet survival to digital quality backbone - Engineer News Network\" \/>\n<meta property=\"og:description\" content=\"Tim\u00a0Wischeropp makes the point that\u00a0additive manufacturing (AM) has earned its place in production. Now it needs the quality infrastructure to match. Not more complexity. Not more dashboards. A backbone. A discipline. A simpler, more industrial way of proving\u00a0(and improving)\u00a0quality Metal additive manufacturing has crossed an important threshold. It is no longer &#8216;promising&#8217;. 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Now it needs the quality infrastructure to match. Not more complexity. Not more dashboards. A backbone. A discipline. A simpler, more industrial way of proving\u00a0(and improving)\u00a0quality Metal additive manufacturing has crossed an important threshold. It is no longer &#8216;promising&#8217;. 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