{"id":131675,"date":"2025-10-22T16:20:56","date_gmt":"2025-10-22T08:20:56","guid":{"rendered":"https:\/\/www.tm-robot.com\/?p=131675"},"modified":"2025-11-12T10:09:54","modified_gmt":"2025-11-12T02:09:54","slug":"case-sharing-enhancing-server-quality-with-ai-inspection-before-shipment","status":"publish","type":"post","link":"https:\/\/www2.tm-robot.com\/en\/case-sharing-enhancing-server-quality-with-ai-inspection-before-shipment\/","title":{"rendered":"Case Sharing: Enhancing Server Quality with AI Inspection Before Shipment"},"content":{"rendered":"<h2><strong>Background and Customer Needs<\/strong><\/h2>\n<p data-start=\"414\" data-end=\"749\">Our client, a well-known electronics manufacturer in Taiwan, specializes in high-volume server production. In the final stage before shipment, every unit must undergo visual inspection to verify the presence, positioning, and condition of key components\u2014such as connectors, cable ties, caps, battery, cable routing, SSDs, and screws.<\/p>\n<p data-start=\"751\" data-end=\"1033\">Previously, this process relied heavily on manual inspection, which was not only time-consuming but also inconsistent due to worker fatigue. The increasing complexity of server configurations further amplified the risk of undetected defects, quality variations, and costly rework.<\/p>\n<p data-start=\"1035\" data-end=\"1112\">The customer required a reliable and scalable inspection system that could:<\/p>\n<ul>\n<li data-start=\"1115\" data-end=\"1181\">Perform consistent visual checks across multiple component types<\/li>\n<li data-start=\"1184\" data-end=\"1224\">Reduce human error and inspection time<\/li>\n<li data-start=\"1227\" data-end=\"1266\">Ensure stable quality before delivery<\/li>\n<\/ul>\n<h2><strong>Challenges<\/strong><\/h2>\n<p data-start=\"1293\" data-end=\"1389\">Although SOPs were in place, the manual inspection process faced the following key challenges:<\/p>\n<ul>\n<li data-start=\"1392\" data-end=\"1497\"><strong data-start=\"1392\" data-end=\"1419\">Fatigue-related errors:<\/strong> Human inspectors often missed subtle issues, especially during long shifts.<\/li>\n<li data-start=\"1500\" data-end=\"1590\"><strong data-start=\"1500\" data-end=\"1524\">Lack of consistency:<\/strong> Judgment varied between operators, impacting quality stability.<\/li>\n<li data-start=\"1593\" data-end=\"1690\"><strong data-start=\"1593\" data-end=\"1619\">Non-traceable process:<\/strong> No systematic method existed to record or trace inspection outcomes.<\/li>\n<li data-start=\"1693\" data-end=\"1812\"><strong data-start=\"1693\" data-end=\"1722\">Complexity of components:<\/strong> The wide range of parts and configurations made visual checking difficult to standardize.<\/li>\n<\/ul>\n<p data-start=\"1814\" data-end=\"1950\">These issues underscore the need for an automated solution that could ensure repeatable accuracy and reduce dependence on manual labor.<\/p>\n<h2><strong>Solution<\/strong><\/h2>\n<p data-start=\"1975\" data-end=\"2164\">To improve inspection performance, the manufacturer implemented a robotic arm solution using the <strong data-start=\"2060\" data-end=\"2075\">TM AI Cobot<\/strong>, which is integrated with a built-in vision system, and a powerful software called <strong>TM AI+ Trainer<\/strong>.<\/p>\n<h3 data-start=\"2166\" data-end=\"2195\"><strong data-start=\"2170\" data-end=\"2193\">Inspection Process:<\/strong><\/h3>\n<ul>\n<li data-start=\"2198\" data-end=\"2314\">The AI model was trained using image datasets labeled as \u201cOK\u201d and \u201cNG\u201d based on multiple server component samples.<\/li>\n<li data-start=\"2317\" data-end=\"2494\">After capturing an image of the server, the AI model classifies each area (e.g., connector, battery, cable tie) to determine whether the part is present, correct, or abnormal.<\/li>\n<li data-start=\"2497\" data-end=\"2623\">If an abnormality (NG) is detected, the system immediately flags the unit and removes it from the line for further handling.<\/li>\n<\/ul>\n<h3 data-start=\"2625\" data-end=\"2658\"><strong data-start=\"2629\" data-end=\"2656\">Key Inspection Targets:<\/strong><\/h3>\n<ul>\n<li data-start=\"2661\" data-end=\"2702\">Connector, cap, and cable tie detection<\/li>\n<li data-start=\"2705\" data-end=\"2741\">Battery presence and cable routing<\/li>\n<li data-start=\"2744\" data-end=\"2779\">SSD and screw presence verification<\/li>\n<\/ul>\n<h2><strong>AI Model Training<\/strong><\/h2>\n<ul>\n<li data-start=\"2815\" data-end=\"2853\"><strong data-start=\"2815\" data-end=\"2836\">AI Function Used:<\/strong> Classification<\/li>\n<li data-start=\"2856\" data-end=\"2923\"><strong data-start=\"2856\" data-end=\"2872\">Data Source:<\/strong> Labeled images captured directly from production<\/li>\n<li data-start=\"2926\" data-end=\"2963\"><strong data-start=\"2926\" data-end=\"2942\">Training Method:<\/strong> Standard supervised training with categorized image sets<\/li>\n<\/ul>\n<p><img loading=\"lazy\" class=\"alignnone size-large wp-image-132196\" src=\"https:\/\/tm-robot.oss-cn-hongkong.aliyuncs.com\/wp-content\/uploads\/2025\/10\/Server-Inspection_02-1024x538.png\" alt=\"\" width=\"1024\" height=\"538\" srcset=\"https:\/\/tm-robot.oss-cn-hongkong.aliyuncs.com\/wp-content\/uploads\/2025\/10\/Server-Inspection_02-1024x538.png 1024w, https:\/\/tm-robot.oss-cn-hongkong.aliyuncs.com\/wp-content\/uploads\/2025\/10\/Server-Inspection_02-300x158.png 300w, https:\/\/tm-robot.oss-cn-hongkong.aliyuncs.com\/wp-content\/uploads\/2025\/10\/Server-Inspection_02-768x404.png 768w, https:\/\/tm-robot.oss-cn-hongkong.aliyuncs.com\/wp-content\/uploads\/2025\/10\/Server-Inspection_02-360x189.png 360w, https:\/\/tm-robot.oss-cn-hongkong.aliyuncs.com\/wp-content\/uploads\/2025\/10\/Server-Inspection_02-1536x807.png 1536w, https:\/\/tm-robot.oss-cn-hongkong.aliyuncs.com\/wp-content\/uploads\/2025\/10\/Server-Inspection_02.png 1600w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/p>\n<p><img loading=\"lazy\" class=\"alignnone size-large wp-image-132187\" src=\"https:\/\/tm-robot.oss-cn-hongkong.aliyuncs.com\/wp-content\/uploads\/2025\/10\/Server-Inspection_01-1024x576.png\" alt=\"\" width=\"1024\" height=\"576\" srcset=\"https:\/\/tm-robot.oss-cn-hongkong.aliyuncs.com\/wp-content\/uploads\/2025\/10\/Server-Inspection_01-1024x576.png 1024w, https:\/\/tm-robot.oss-cn-hongkong.aliyuncs.com\/wp-content\/uploads\/2025\/10\/Server-Inspection_01-300x169.png 300w, https:\/\/tm-robot.oss-cn-hongkong.aliyuncs.com\/wp-content\/uploads\/2025\/10\/Server-Inspection_01-768x432.png 768w, https:\/\/tm-robot.oss-cn-hongkong.aliyuncs.com\/wp-content\/uploads\/2025\/10\/Server-Inspection_01-360x203.png 360w, https:\/\/tm-robot.oss-cn-hongkong.aliyuncs.com\/wp-content\/uploads\/2025\/10\/Server-Inspection_01.png 1280w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/p>\n<h2><strong>Results &amp; Benefits<\/strong><\/h2>\n<ul>\n<li data-start=\"3080\" data-end=\"3178\"><strong data-start=\"3080\" data-end=\"3115\">Parallel multi-point detection:<\/strong> Simultaneous inspection of multiple parts reduced cycle time<\/li>\n<li data-start=\"3181\" data-end=\"3278\"><strong data-start=\"3181\" data-end=\"3204\">Higher consistency:<\/strong> AI provided uniform inspection judgment regardless of shift or operator<\/li>\n<li data-start=\"3281\" data-end=\"3385\"><strong data-start=\"3281\" data-end=\"3307\">Improved traceability:<\/strong> All inspection results were recorded digitally for tracking and QA analysis<\/li>\n<li data-start=\"3388\" data-end=\"3471\"><strong data-start=\"3388\" data-end=\"3428\">Reduced rework and after-sales risk:<\/strong> Only qualified servers proceed to shipment<\/li>\n<\/ul>\n<h2><strong>Conclusion<\/strong><\/h2>\n<p data-start=\"3498\" data-end=\"3839\">With TM AI Cobot as an automated inspection solution, the customer successfully replaced time-intensive manual checks with a reliable AI-powered system. This not only enhanced inspection efficiency and traceability but also ensured higher product quality at the final stage\u2014reinforcing trust in the company\u2019s server manufacturing excellence.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Background and Customer Needs Our client, a well-known electronics manufacturer in Taiwan, specializes in high-volume server production. In the final stage before shipment, every unit must undergo visual inspection to verify the presence, positioning, and condition of key components\u2014such as connectors, cable ties, caps, battery, cable routing, SSDs, and screws. Previously, this process relied heavily [&hellip;]<\/p>\n","protected":false},"author":84,"featured_media":132071,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[2935],"tags":[],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v16.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Case Sharing: Enhancing Server Quality with AI Inspection Before Shipment | Techman Robot<\/title>\n<meta name=\"description\" content=\"Our client, a well-known electronics manufacturer in Taiwan, specializes in high-volume server production. 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