{"id":3029,"date":"2025-07-07T15:31:01","date_gmt":"2025-07-07T07:31:01","guid":{"rendered":"https:\/\/www.rzautoassembly.com\/?p=3029"},"modified":"2025-07-07T15:31:01","modified_gmt":"2025-07-07T07:31:01","slug":"edge-computing-and-fog-computing-enabling-intelligence-to-burst-locally-at-production-sites","status":"publish","type":"post","link":"https:\/\/www.rzautoassembly.com\/es\/edge-computing-and-fog-computing-enabling-intelligence-to-burst-locally-at-production-sites\/","title":{"rendered":"Edge Computing and Fog Computing: Enabling Intelligence to \u201cBurst Locally\u201d at Production Sites"},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_73 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1 ez-toc-heading-level-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.rzautoassembly.com\/es\/edge-computing-and-fog-computing-enabling-intelligence-to-burst-locally-at-production-sites\/#Edge_Computing_and_Fog_Computing_Enabling_Intelligence_to_%E2%80%9CBurst_Locally%E2%80%9D_at_Production_Sites\" title=\"Edge Computing and Fog Computing: Enabling Intelligence to \u201cBurst Locally\u201d at Production Sites\">Edge Computing and Fog Computing: Enabling Intelligence to \u201cBurst Locally\u201d at Production Sites<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.rzautoassembly.com\/es\/edge-computing-and-fog-computing-enabling-intelligence-to-burst-locally-at-production-sites\/#%E4%B8%80%E3%80%81Technical_Essence_From_%E2%80%9CDistant_Water_Cannot_Quench_Near_Thirst%E2%80%9D_to_%E2%80%9CLocalized_Resource_Utilization%E2%80%9D\" title=\"\u4e00\u3001Technical Essence: From \u201cDistant Water Cannot Quench Near Thirst\u201d to \u201cLocalized Resource Utilization\u201d\">\u4e00\u3001Technical Essence: From \u201cDistant Water Cannot Quench Near Thirst\u201d to \u201cLocalized Resource Utilization\u201d<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.rzautoassembly.com\/es\/edge-computing-and-fog-computing-enabling-intelligence-to-burst-locally-at-production-sites\/#%E4%BA%8C%E3%80%81Industry_Practices_Penetration_from_Discrete_Manufacturing_to_Process_Industries\" title=\"\u4e8c\u3001Industry Practices: Penetration from Discrete Manufacturing to Process Industries\">\u4e8c\u3001Industry Practices: Penetration from Discrete Manufacturing to Process Industries<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.rzautoassembly.com\/es\/edge-computing-and-fog-computing-enabling-intelligence-to-burst-locally-at-production-sites\/#%E4%B8%89%E3%80%81Technological_Evolution_Lightweight_Low-Power_and_Ubiquitous\" title=\"\u4e09\u3001Technological Evolution: Lightweight, Low-Power, and Ubiquitous\">\u4e09\u3001Technological Evolution: Lightweight, Low-Power, and Ubiquitous<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.rzautoassembly.com\/es\/edge-computing-and-fog-computing-enabling-intelligence-to-burst-locally-at-production-sites\/#%E5%9B%9B%E3%80%81Future_Vision_Intelligent_Pyramid_of_Cloud-Edge-Terminal_Collaboration\" title=\"\u56db\u3001Future Vision: Intelligent Pyramid of Cloud-Edge-Terminal Collaboration\">\u56db\u3001Future Vision: Intelligent Pyramid of Cloud-Edge-Terminal Collaboration<\/a><\/li><\/ul><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h1><span class=\"ez-toc-section\" id=\"Edge_Computing_and_Fog_Computing_Enabling_Intelligence_to_%E2%80%9CBurst_Locally%E2%80%9D_at_Production_Sites\"><\/span><span style=\"font-family: 'times new roman', times, serif;\"><strong><b>Edge Computing and Fog Computing: Enabling Intelligence to \u201cBurst Locally\u201d at Production Sites<\/b><\/strong><\/span><span class=\"ez-toc-section-end\"><\/span><\/h1>\n<p><img fetchpriority=\"high\" decoding=\"async\" class=\"size-medium wp-image-3031 aligncenter\" src=\"https:\/\/www.rzautoassembly.com\/wp-content\/smush-webp\/2025\/07\/\u975e\u6807\u81ea\u52a8\u5316\u8bbe\u5907\u5e7f\u544a\u521b\u610f-361-1-300x194.png.webp\" alt=\"\" width=\"300\" height=\"194\" srcset=\"https:\/\/www.rzautoassembly.com\/wp-content\/smush-webp\/2025\/07\/\u975e\u6807\u81ea\u52a8\u5316\u8bbe\u5907\u5e7f\u544a\u521b\u610f-361-1-300x194.png.webp 300w, https:\/\/www.rzautoassembly.com\/wp-content\/smush-webp\/2025\/07\/\u975e\u6807\u81ea\u52a8\u5316\u8bbe\u5907\u5e7f\u544a\u521b\u610f-361-1-1024x663.png.webp 1024w, https:\/\/www.rzautoassembly.com\/wp-content\/smush-webp\/2025\/07\/\u975e\u6807\u81ea\u52a8\u5316\u8bbe\u5907\u5e7f\u544a\u521b\u610f-361-1-768x497.png.webp 768w, https:\/\/www.rzautoassembly.com\/wp-content\/uploads\/2025\/07\/\u975e\u6807\u81ea\u52a8\u5316\u8bbe\u5907\u5e7f\u544a\u521b\u610f-361-1-18x12.png 18w, https:\/\/www.rzautoassembly.com\/wp-content\/smush-webp\/2025\/07\/\u975e\u6807\u81ea\u52a8\u5316\u8bbe\u5907\u5e7f\u544a\u521b\u610f-361-1.png.webp 1335w\" sizes=\"(max-width: 300px) 100vw, 300px\" \/><\/p>\n<p>In the \u201cdata\u00a0 (data )\u201d of smart manufacturing, edge computing and fog computing are becoming key technologies to solve \u201ccloud latency\u201d and \u201cdata overload,\u201d constructing a new \u201ccloud-edge collaboration\u201d computing architecture. Gartner predicts that by 2025, 75% of industrial data will be processed at the edge, with its value lying in making intelligent decisions \u201ccloser to the site and more responsive.\u201d<\/p>\n<h3><span class=\"ez-toc-section\" id=\"%E4%B8%80%E3%80%81Technical_Essence_From_%E2%80%9CDistant_Water_Cannot_Quench_Near_Thirst%E2%80%9D_to_%E2%80%9CLocalized_Resource_Utilization%E2%80%9D\"><\/span><strong><b>\u4e00\u3001Technical Essence: From \u201cDistant Water Cannot Quench Near Thirst\u201d to \u201cLocalized Resource Utilization\u201d<\/b><\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>The intelligent warehousing system at Foxconn\u2019s Shenzhen plant reveals the core advantages of edge computing: Each AGV robot is equipped with an edge computing gateway, processing data from 16-line LiDAR and 8 sets of ultrasonic sensors in real time, completing path planning and obstacle avoidance decisions within 20ms\u201425 times faster than the 500ms response of traditional cloud processing, with 30% higher warehouse logistics efficiency. This model of \u201clocal real-time decision-making + cloud strategy optimization\u201d demonstrates irreplaceability in latency-sensitive scenarios:<\/p>\n<ul>\n<li><b><\/b><strong><b>Precision Requirements<\/b><\/strong>: In OPPO\u2019s Dongguan camera module production line, the edge computing box processes 12-megapixel quality inspection images in real time, using the YOLOv8 algorithm to achieve a defect recognition speed of 200 frames\/second with a miss detection rate &lt;0.01%, 4 times faster than cloud processing.<\/li>\n<li><b><\/b><strong><b>Privacy Protection<\/b><\/strong>: In a military enterprise\u2019s missile component production line, edge nodes complete encryption of 300+ process parameters locally, transmitting only desensitized statistical data to the cloud, reducing data leakage risk by 95%.<\/li>\n<li><b><\/b><strong><b>Network Failure Tolerance<\/b><\/strong>: Sany Heavy Industry\u2019s intelligent tower crane stores 72 hours of operation data via edge computing modules. Even during network outages, it realizes anti-collision warnings based on local models, reducing construction accident rates by 60%.<\/li>\n<\/ul>\n<h3><span class=\"ez-toc-section\" id=\"%E4%BA%8C%E3%80%81Industry_Practices_Penetration_from_Discrete_Manufacturing_to_Process_Industries\"><\/span><strong><b>\u4e8c\u3001Industry Practices: Penetration from Discrete Manufacturing to Process Industries<\/b><\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>In process manufacturing, Schneider Electric\u2019s Shanghai plant achieves refined energy management through a fog computing architecture (a distributed computing layer between edge and cloud) in its intelligent power distribution system: Workshop-level fog nodes analyze the power load of 2,000 devices in real time, dynamically adjusting the start-stop strategy of air compressors (accounting for 30% of factory energy consumption), achieving 18% energy savings while ensuring production\u2014equivalent to reducing 1,500 tons of CO\u2082 emissions annually. More innovatively, fog nodes achieve data mutual trust via industrial blockchain, automatically coordinating energy allocation for adjacent production lines, reducing electricity costs during peak-valley pricing periods by 25%.<\/p>\n<p>In the precision assembly scenario of discrete manufacturing, edge computing applications at Siemens\u2019 German plant have entered the \u201cmicrometer era\u201d: At the high-precision bearing assembly station, edge servers parse position data from a 3D vision system (accuracy \u00b12\u03bcm) in real time, combining pressure feedback (resolution 0.1N) from force-controlled robots to dynamically adjust assembly angles, reducing bearing concentricity error from 5\u03bcm to 1.5\u03bcm and increasing assembly yield from 92% to 98.5%. This precision breakthrough granted the plant exclusive supply qualification for a German luxury car brand.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"%E4%B8%89%E3%80%81Technological_Evolution_Lightweight_Low-Power_and_Ubiquitous\"><\/span><strong><b>\u4e09\u3001Technological Evolution: Lightweight, Low-Power, and Ubiquitous<\/b><\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>With the popularization of lightweight communication technologies like 5G RedCap and NB-IoT, edge computing nodes are shrinking from \u201ccabinet servers\u201d to \u201cpalm size.\u201d Huawei\u2019s industrial edge computing gateway (10cm\u00d710cm) integrates AI computing power (2TOPS), 5G communication, and Beidou positioning, supporting stable operation in -40\u2103~70\u2103 environments. Over 5,000 units have been deployed at Qingdao Port\u2019s intelligent terminal, enabling millimeter-level positioning and millisecond-level response for container cranes.<\/p>\n<p>In the low-power field, a domestic semiconductor enterprise developed a \u201cpassive edge node\u201d that operates without external power via energy harvesting technology (vibration\/thermal difference power generation). After deploying it on equipment bearings, it collects vibration data in real time for local analysis, warning of lubrication failure risks 7 days in advance, extending bearing life by 30%. This technology has achieved scaled applications in wind power, petrochemicals, and other fields.<\/p>\n<h3><span class=\"ez-toc-section\" id=\"%E5%9B%9B%E3%80%81Future_Vision_Intelligent_Pyramid_of_Cloud-Edge-Terminal_Collaboration\"><\/span><strong><b>\u56db\u3001Future Vision: Intelligent Pyramid of Cloud-Edge-Terminal Collaboration<\/b><\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<p>Future smart manufacturing will form a four-tier \u201ccloud-fog-edge-terminal\u201d architecture:<\/p>\n<ul>\n<li><b><\/b><strong><b>Cloud Layer<\/b><\/strong>: Responsible for long-term data storage and strategic decisions (e.g., annual capacity planning, supply chain layout).<\/li>\n<li><b><\/b><strong><b>Fog Layer<\/b><\/strong>: Handles regional collaboration (e.g., workshop-level energy scheduling, multi-line load balancing).<\/li>\n<li><b><\/b><strong><b>Edge Layer<\/b><\/strong>: Executes real-time control and local optimization (e.g., equipment fault diagnosis, real-time quality inspection).<\/li>\n<li><b><\/b><strong><b>Terminal Layer<\/b><\/strong>: Focuses on data collection and execution (e.g., sensors, actuators, intelligent terminals).<\/li>\n<\/ul>\n<p>This hierarchical architecture precisely releases data value: 90% of real-time control data is processed at the edge, 70% of regional collaboration data circulates in the fog layer, and only 30% of key decision data is uploaded to the cloud. When edge computing deeply integrates with digital twins, every workstation and device in the factory will have \u201clocal intelligence,\u201d forming an organic whole of \u201cmicro-intelligent units + macro-intelligent systems,\u201d driving smart manufacturing from \u201ccloud-driven\u201d to \u201csite-autonomous\u201d and enabling intelligence to take root at the production frontline.<\/p>\n<p>&#8220;<a href=\"https:\/\/www.rzautoassembly.com\/es\/products\/\">smartrend manufacturing group<\/a>&#8221;\u00a0&#8220;<a href=\"https:\/\/www.rzautoassembly.com\/es\/products\/\">smart paint manufacturing sdn bhd<\/a>&#8221;\u00a0&#8220;<a href=\"https:\/\/www.rzautoassembly.com\/es\/products\/\">smart meter manufacturing companies in india<\/a>&#8220;<\/p>","protected":false},"excerpt":{"rendered":"<p>Edge Computing and Fog Computing: Enabling Intelligence to \u201cBurst Locally\u201d at Production Sites In the \u201cdata\u00a0 (data )\u201d of smart manufacturing, edge computing and fog computing are becoming key technologies to solve \u201ccloud latency\u201d and \u201cdata overload,\u201d constructing a new \u201ccloud-edge collaboration\u201d computing architecture. Gartner predicts that by 2025, 75% of industrial data will be [\u2026]<\/p>","protected":false},"author":1,"featured_media":3030,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[126,1,124],"tags":[],"class_list":["post-3029","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-company-news","category-news","category-technology"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.rzautoassembly.com\/es\/wp-json\/wp\/v2\/posts\/3029","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.rzautoassembly.com\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.rzautoassembly.com\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.rzautoassembly.com\/es\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.rzautoassembly.com\/es\/wp-json\/wp\/v2\/comments?post=3029"}],"version-history":[{"count":0,"href":"https:\/\/www.rzautoassembly.com\/es\/wp-json\/wp\/v2\/posts\/3029\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.rzautoassembly.com\/es\/wp-json\/wp\/v2\/media\/3030"}],"wp:attachment":[{"href":"https:\/\/www.rzautoassembly.com\/es\/wp-json\/wp\/v2\/media?parent=3029"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.rzautoassembly.com\/es\/wp-json\/wp\/v2\/categories?post=3029"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.rzautoassembly.com\/es\/wp-json\/wp\/v2\/tags?post=3029"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}