RII Track 2 FEC: Enabling Factory to Factory (F2F) Networking for Future Manufacturing

网络基础设施和人工智能(AI)是南卡罗来纳州(SC)、西弗吉尼亚州(WV)和美国智能制造的核心组件。为了推动工业的根本转型，工厂必须安全地超越它们的物理边界。这些未来工厂(FF)消费和创造跨学科的知识，以及锻造创新技术改造的能力。该项目引入了一种新的未来网络制造模式--工厂到工厂(F2F)网络框架。面向自动化，F2F网络需要利益相关者之间的互操作性以及高效的数据、信息和知识理解系统。由南卡罗来纳大学和西弗吉尼亚大学领导的学术界和工业界之间的这种合作将在SC和WV产生先进的智能制造技术和受过教育的高技能劳动力。此外，它还将为未来的制造技术创建一个蓝图模型，该模型可以与F2F网络集成，以提高美国各地的小规模和工业制造能力。为了扩大我们的劳动力基础设施，我们将为智能制造建立一个终身学习渠道，范围从K-12教育、高等教育，到为学者和工业专业人员提供的专业发展支持。特别是，我们将为K-12学生创建在线学习资源和面向STEM的智能制造暑期项目，并通过我们的行业合作伙伴为大学生和研究生提供实习机会。该项目将适应、增强和集成信息技术(IT)和运营技术(OT)，如实时安全传感、高性能计算、无线通信和人工智能，以支持F2F分布式智能制造系统的流程优化。只有将制造过程的专业知识与新出现的硬件和软件技术融合在一起，才能实现融合和真正的进步。该项目的重点是制造知识：(1)作为一种新的分布式系统间制造知识表示的产品制造DNA的自主特征提取和识别；(2)结合产品生命周期内的跨平台仿真结果的交互式网络空间的体系结构；(3)过程监控过程中的数据驱动控制理论，导致快速自主决策取代人工输入/输出模块；(4)稳健的商业模型和运筹学(面向信息服务)，涉及分布式子系统之间的自主关键性能指标(KPI)分解和快速反馈控制回路。这将为实时生产信息共享和控制平台奠定基础，并促进网络化系统之间制造知识的生成和利用，以应对制造管理挑战。此外，它还允许在这些高度协作的网络化智能制造系统的开发和决策过程中进行人工干预和互操作。该项目将展示几种新的网络制造实施，并建立一个通向通用数字F2F标准的路线图。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Cyber infrastructure and artificial intelligence (AI) are core components of smart manufacturing in South Carolina (SC), West Virginia (WV), and the United States. To drive radical transformation of industry, factories must securely expand beyond their physical boundaries. These Future Factories (FF) consume and create interdisciplinary knowledge along with the ability to forge innovative technological transformations. This project introduces a novel future cyber-manufacturing paradigm – the Factory-to-Factory (F2F) network framework. Geared towards automation, F2F networks require interoperability of stakeholders and efficient understanding systems for data, information, and knowledge. This collaboration between academia – led by the University of South Carolina and West Virginia University - and industry will produce advanced smart manufacturing technologies and an educated upskilled workforce in SC and WV. Furthermore, it will create a blueprint model for future manufacturing technologies that can be integrated with a F2F network to increase small-scale and industrial manufacturing capabilities across the US. To expand our workforce infrastructure, we will establish a lifelong learning pipeline for smart manufacturing ranging from K-12 education, higher education, to professional development support for scholars and industrial professionals. Particularly, we will create online learning resources and STEM-oriented smart manufacturing summer programs for K-12 students and provide internships for college and graduate students through our industrial partners. This project will adapt, enhance, and integrate informational technologies (IT) and operational technologies (OT) such as real-time secured sensing, high performance computing, wireless communications, and AI, to support process optimization among distributed smart manufacturing systems for F2F. Convergence and true progress can only be achieved by fusing expert knowledge of manufacturing processes with newly emerged hardware and software technologies. The project focuses on manufacturing knowledge stemming from: (1) autonomous feature extraction and recognition from product ‘manufacturing DNAs’ as a novel manufacturing knowledge representation among distributed systems, (2) architecture of interactive cyber spaces that combines cross-platform simulation results within product lifecycles, (3) data-driven control theories during process monitoring leading to rapid autonomous decision-making in replacement of manual input/output modules, and (4) robust business models and operations research (information service-oriented) concerning autonomous Key Performance Indicator (KPI) decomposition among distributed sub-systems and rapid feedback control loops. This will build a foundation for real-time production information sharing and control platforms and facilitate manufacturing knowledge generation and utilization among networked systems to address manufacturing management challenges. Furthermore, it enables human interventions and interoperations in the development and decision-making process of these highly collaborative networked smart manufacturing systems. This project will showcase several novel cyber manufacturing implementations and establish a roadmap towards a universal digital F2F standard.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.