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.

该赠款支持对通过数字连接机，人类和制造产品对添加剂制造的根本转变的基本研究。添加剂制造已使从制造方法的传统设计转变为设计的新范式转变。当我们进入超越添加剂制造的智能未来制造业的新时代，添加剂制造是必要的。一个有希望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）数据过程的收敛，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方式，这些方式可以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添加剂制造业打开了新的过渡之门，使事物和数字双胞胎的真正互联网，与机器人，计算机和人类以及我们在工厂中生产的每种产品之间的工厂中的设备和机器连接。该赠款还将支持为了提高制造业劳动力，K-12，本科生和研究生以及公众的教育活动，从而极大地影响了各个年龄段和背景的各种人群。对网络物理生产制造的转换要求通过分布式传感超出与人类合作的数字连接机器和机器人的当前状态的分布式传感。该项目旨在通过嵌入无线传感器并使用AI和ML技术进行预测性分析和健康监测，以实现前所未有的无线指纹识别和增添加零件的感测。该项目提出了一种涉及四个核心研究任务的整体方法：1）研究添加剂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）为证明，可以使用毫米波天线对嵌入式的被动传感器信号无线感知，4）可以快速使用ML算法来快速监测和评估制成品的状态。该项目有可能实现下一代网络物理生产系统。 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.

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