FMSG: Cyber: Perceptual and Cognitive Additive Manufacturing (PCAM)

该基金支持通过数字化连接机器、人类和制造产品，对增材制造进行根本性变革的基础研究。增材制造实现了从传统的为制造而设计的方法到为设计而制造的新范式转变。随着我们进入超越增材制造的智能未来制造新时代，增材制造的根本性变革是必要的。一个很有前途的解决方案是无线嵌入式传感器与人工智能（AI）和机器学习（ML）数据处理的融合，这可以改变人们与制造过程、工厂运营、优化效率和异常系统检测的交互方式，从而提供有关被评估组件和系统的关键信息。该项目为感知和认知增材制造打开了一扇新的过渡之门，实现了真正的物联网和数字孪生，将工厂中的设备和机器与机器人、计算机和人类以及我们在工厂生产的每一件产品连接起来。这笔赠款还将支持教育活动，以提高制造业劳动力、K-12、本科生和研究生以及公众的技能，从而对所有年龄和背景的不同人群产生重大影响。向网络物理生产制造的转型需要通过分布式传感进行先进的过程监控，而不仅仅是数字连接机器和机器人与人类合作的现状。该项目旨在通过嵌入无线传感器，并使用人工智能和机器学习技术进行预测分析和健康监测，从而实现前所未有的无线指纹识别和增材制造部件的传感。本项目提出了一个整体的方法，涉及四个核心研究任务：1)研究在增材制造过程中嵌入传感器的影响；2)设计可嵌入式声学传感器，在制造过程中插入，读取物理参数；3)证明嵌入式无源传感器信号可以使用毫米波天线无线感知，4)使用ML算法快速监测和评估制造产品的状态。该项目具有实现下一代网络物理生产系统的潜力。这份“未来制造”合同由英国工程局（ENG）的电气、通信和网络系统部（ECCS）以及英国计算机和信息科学与工程局（CISE）的计算机和网络系统部（CNS）提供支持。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This grant supports fundamental research on a radical transformation of additive manufacturing through digitally connecting machines, humans, and manufactured products. Additive manufacturing has enabled a new paradigm shift from conventional design for manufacturing approaches into manufacturing for design. A fundamental change in additive manufacturing is necessary as we enter a new era of intelligent future manufacturing beyond additive manufacturing. A promising solution is the convergence of wireless embedded sensors with artificial intelligence (AI) and machine learning (ML) data processes, which can transform the way people interact with manufacturing processes, factory operations, optimizing efficiency, and anomaly system detection that could provide critical information about evaluated components and systems. This project opens a new transitional door to perceptive and cognitive additive manufacturing, enabling true internet of things and digital twin, connecting devices and machines in factories with robots, computers, and humans, and every product we manufacture in factories. The grant will also support educational activities to upskill the manufacturing workforce, K-12, undergraduate and graduate students, and the public, significantly influencing diverse populations of all ages and backgrounds. Transformation to cyber-physical production manufacturing demands advanced process monitoring through distributed sensing beyond the current state of digitally connected machines and robots collaborating with humans. This project seeks to enable unprecedented wireless fingerprinting and sensing of additively manufactured parts by embedding wireless sensors and performing predictive analysis and health monitoring using AI and ML techniques. This project proposes a holistic approach involving four core research tasks: 1) to study the effects of embedding sensors during additive manufacturing; 2) to design embeddable acoustic sensors and insert them during the manufacturing process to read physical parameters; 3) to prove that embedded passive sensor signals can be sensed wirelessly using millimeter-wave antennas, and 4) to quickly monitor and evaluate the state of manufactured products using ML algorithms. This project has the potential to enable next-generation cyber-physical production systems. This Future Manufacturing award is supported by the Division of Electrical, Communications and Cyber Systems (ECCS) in the Directorate for Engineering (ENG) and the Division of Computer and Network Systems (CNS) of the Directorate for Computer and Information Science and Engineering (CISE).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.