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

FMSG：网络：感知和认知增材制造 (PCAM)

• 批准号: 2229155
• 负责人: Daewon Kim
• 金额: $ 50万
• 依托单位: Embry-Riddle Aeronautical University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-15 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2229155&HistoricalAwards=false
• 关键词: FMSG; Cyber; Perceptual; Cognitive; Additive

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.

该补助金支持通过数字连接机器，人类和制造产品来实现增材制造的根本转型的基础研究。增材制造已经实现了从传统的为制造而设计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将无线嵌入式传感器与人工智能（AI）和机器学习（ML）数据流程融合在一起，这可以改变人们与制造流程、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中制造的每一种产品连接起来。该补助金还将支持教育活动，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，显著影响所有年龄和背景的不同人群。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，超越当前数字连接机器和机器人与人类合作的状态。该项目旨在通过嵌入无线传感器并使用AI和ML技术进行预测分析和健康监测，实现前所未有的无线指纹识别和增材制造部件的传感。该项目提出了一种整体方法，涉及四个核心研究任务：1）研究增材制造过程中嵌入传感器的影响; 2）设计可嵌入的声学传感器，并在制造过程中插入它们以读取物理参数; 3）为了证明可以使用毫米波天线无线地感测嵌入的无源传感器信号，（4）利用机器学习算法对制造产品的状态进行快速监测和评估。该项目有可能实现下一代网络物理生产系统。这个未来制造奖是由电气，通信和网络系统（ECCS）在工程局（ENG）和计算机和信息科学与工程局（CISE）的计算机和网络系统（CNS）司该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的评估被认为值得支持。影响审查标准。

项目成果

Electrode filling using capillary action of 3D printed elastomer microchannels

利用 3D 打印弹性体微通道的毛细管作用填充电极

• DOI: 10.1117/12.2658146
• 发表时间: 2023
• 期刊: SPIE
• 作者: Stark, Taylor;Kim, Daewon
• 通讯作者: Kim, Daewon

Wave-based sensor responses with embedded electrode layouts

• DOI: 10.1117/12.2658076
• 发表时间: 2023-04
• 作者: Rishikesh Srinivasaraghavan Govindarajan;F. Madiyar;Daewon Kim

Hydrophilic surface morphology for intricate conductive coatings

• DOI: 10.1117/12.2658143
• 发表时间: 2023-04
• 作者: T. Stark;Stanislav Sikulskyi;Rishikesh Srinivasaraghavan Govindarajan;Daewon Kim

On the performance of PVDF based piezoelectric sensor with microstructures

• DOI: 10.1117/12.2658072
• 发表时间: 2023-04
• 作者: Rishikesh Srinivasaraghavan Govindarajan;T. Stark;F. Madiyar;Daewon Kim

Additive Manufacturing of Photocurable PVDF-Based Capacitive Sensor

基于光固化 PVDF 的电容式传感器的增材制造

• DOI: 10.1115/smasis2023-111151
• 发表时间: 2023
• 期刊: American Society of Mechanical Engineers
• 作者: Srinivasaraghavan Govindarajan, Rishikesh;Ren, Zefu;Madiyar, Foram;Kim, Daewon
• 通讯作者: Kim, Daewon