--- 格式版本: 2 标题: "Foxconn Expands Blackwell Production with New Factories in US, Mexico, and Taiwan | NVIDIA Blog" 原文链接: "https://blogs.nvidia.com/blog/foxconn-blackwell-omniverse/" 发布日期: "2026-06-30" 发布时间校准状态: "found" 发布时间来源: "llm:strict_original_body" 发布时间证据: "time class=related-news-date nvidia-article-date datetime=2026-06-30T08:00:57-07:00: Jun 30, 2026" 发布时间校准原因: "该日期来自HTML metadata中的article-date字段，位于标题附近，符合文章发布时间的特征。" 发布时间校准置信度: "1" 发布时间候选数量: 36 发布时间严格候选数量: 12 发布时间原页读取状态: "原页面来自已抓取 HTML" 发布时间未找到原因: "候选日期无效或 LLM 未确认" 发布时间校准时间: "2026-07-20T14:21:15+08:00" 发现时间: "2026-07-20T09:26:50+08:00" 入库时间: "2026-07-20T06:30:10.222Z" 来源平台: "NVIDIA Blog 搜索" 搜索渠道: "source_template" 搜索词: "https://blogs.nvidia.com/?s=Foxconn" 匹配关键词: [] 相关厂家: - "Foxconn" - "NVIDIA" 相关专家: [] 内容类型: "网页" 抓取工具: "AgentKey Scrape" 清洗工具: "AgentKey Markdown + LLM 正文裁剪" 原始附件: [] AI优质: "否" AI打分: 48 AI分档: "非优质" AI质检状态: "不通过" AI打分理由: "正文主要讨论富士康使用NVIDIA Omniverse进行工厂数字孪生和机器人仿真，未涉及超节点/AI Rack/机柜级AI基础设施的架构、部件、互连、供电或散热等技术细节，仅提及Blackwell量产和工厂部署，技术深度不足。" AI质检模型: "qwen3.6-plus" AI质检时间: "2026-07-20T14:30:10+08:00" AI主题相关性: 8 AI来源权威性: 14 AI新颖性: 10 AI技术细节: 4 AI商业部署信号: 8 AI完整性: 4 图片摘要: - "★ ./assets/img-83d2f103.jpg | diagram | 展示基于 Omniverse 的工厂设施数字孪生布局，用于虚拟集成设备与优化空间规划。" - "✗ ./assets/img-1f6575f1.png | diagram | 图片内容涉及 NVIDIA Vera CPU 架构，与正文关于富士康使用 Omniverse 进行工厂规划的主题无关。" - "✗ ./assets/img-3511966c.jpg | photo | 仅为 NVIDIA 品牌标识与建筑实拍，属于品牌宣传/装饰性配图，未展示正文所述的富士康工厂或 Omniverse 应用细节。" - "✗ ./assets/img-e47e99dc.png | diagram | 图片主题涉及推理软件栈与 Token 成本，与正文关于富士康利用 Omniverse 进行工厂建设和 Blackwell 生产的主题不符。" 采集批次: "2026年7月20日9点23分34秒" 采集批次ID: "20260720-092334-062" 去重键: "https://blogs.nvidia.com/blog/foxconn-blackwell-omniverse" --- To meet demand for Blackwell, now in full production, Foxconn, the world’s largest electronics manufacturer, is using [NVIDIA Omniverse](https://www.nvidia.com/en-us/omniverse/). The platform for developing industrial AI simulation applications is helping bring facilities in the U.S., Mexico and Taiwan online faster than ever. Foxconn uses NVIDIA Omniverse to virtually integrate their facility and equipment layouts, [NVIDIA Isaac Sim](https://developer.nvidia.com/isaac/sim) for autonomous robot testing and simulation, and [NVIDIA Metropolis](https://www.nvidia.com/en-us/autonomous-machines/intelligent-video-analytics-platform/) for vision AI. Omniverse enables industrial developers to maximize efficiency through test and optimization in a digital twin before deploying costly change-orders to the physical world. Foxconn expects its Mexico facility alone to deliver significant cost savings and a reduction in kilowatt-hour usage of more than 30% annually. ## World’s Largest Electronics Maker Plans With Omniverse and AI To meet demands at Foxconn, factory planners are building [physical AI](https://www.nvidia.com/en-us/glossary/generative-physical-ai/) -powered robotic factories with Omniverse and NVIDIA AI. The company has built [digital twins](https://www.nvidia.com/en-us/glossary/digital-twin/) with Omniverse that allow their teams to virtually integrate facility and equipment information from leading industry applications, such as Siemens Teamcenter X and Autodesk Revit. Floor plan layouts are optimized first in the digital twin, and planners can locate optimal camera positions that help measure and identify ways to streamline operations with Metropolis visual AI agents. In the construction process, the Foxconn teams use the Omniverse digital twin as the source of truth to communicate and validate the accurate layout and placement of equipment. Virtual integration on Omniverse offers significant advantages, potentially saving factory planners millions by reducing costly change orders in real-world operations. ## Delivering Robotics for Manufacturing With Omniverse Digital Twin Once the digital twin of the factory is built, it becomes a virtual gym for Foxconn’s fleets of autonomous robots including industrial manipulators and autonomous mobile robots. Foxconn’s robot developers can simulate, test and validate their AI robot models in [NVIDIA Isaac Sim](https://developer.nvidia.com/isaac/sim) before deploying to their real world robots. Using Omniverse, Foxconn can simulate robot AIs before deploying to [NVIDIA Jetson-driven autonomous mobile robots](https://www.nvidia.com/en-us/autonomous-machines/). On assembly lines, they can simulate with [Isaac Manipulator](https://developer.nvidia.com/isaac/manipulator) libraries and AI models for automated optical inspection, object identification, defect detection and trajectory planning. Omniverse also enables their facility planners to test and optimize intelligent camera placement before installing in the physical world – ensuring they have complete coverage of the factory floor to support worker safety, and provide the foundation for [visual AI agent frameworks](https://www.nvidia.com/en-us/use-cases/visual-ai-agents/). ## Creating Efficiencies While Building Resilient Supply Chains Using NVIDIA Omniverse and AI, Foxconn plans to replicate its precision production lines across the world. This will enable it to quickly deploy high-quality production facilities that meet unified standards, increasing the company’s competitive edge and adaptability in the market. Foxconn’s ability to rapidly replicate will accelerate its global deployments and enhance its resilience in the supply chain in the face of disruptions, as it can quickly adjust production strategies and reallocate resources to ensure continuity and stability to meet changing demands. Foxconn’s Mexico facility will begin production early next year and the Taiwan location will begin production in December. *Learn more about [Blackwell](https://www.nvidia.com/en-us/data-center/technologies/blackwell-architecture/) and [Omniverse](https://www.nvidia.com/en-us/omniverse/).* ![Why Performance per Watt Is the Ultimate Metric for AI Infrastructure Efficiency](./assets/img-83d2f103.jpg)