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AI Institute: Planning: AI-Enabled Secure and Responsive Smart Manufacturing

人工智能研究院：规划：人工智能赋能的安全响应式智能制造

基本信息

批准号：
2020246
负责人：
Vijay Gupta
金额：
$ 50万
依托单位：
University of Notre Dame
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2022-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2020246&HistoricalAwards=false
关键词：
AI Institute Planning Enabled Secure

项目摘要

Advanced manufacturing is on the cusp of a Fourth Industrial revolution, captured by the term Industry 4.0 or Smart Manufacturing. However, challenges abound in realizing the smart manufacturing paradigm. Rapidly reconfigurable production systems envisaged in smart manufacturing are inherently tied to acquisition of large amounts of continuous streaming data from machines and automated robots on the shop floor, as well as from entities dispersed in the supply-logistics chain, using heterogeneous sensors. The data has to be transmitted over wireless channels with tight latency and security guarantees, and coupled with real-time analysis to allow precise trouble-shooting, coordination, and monitoring. The inescapable conclusion is that to enable smart manufacturing, a tight integration – and, in fact, cross-layer optimization – of manufacturing technologies, robotics and control, networking protocols such as 5G, and machine learning paradigms such as inference on the edge is needed. Achieving this vision is the goal of the institute envisaged in this planning grant. Realizing an effective institute will require experts in advanced manufacturing, AI, sensing, computation, and sensing, as well as collaboration with industry and federal research labs. The major activities in this planning grant aim at developing such a team through a range of activities. The intellectual bulwark of the institute is the enabling of smart manufacturing through a tight integration and cross-layer optimization of manufacturing technologies, networking protocols such as 5G, robotics and control, and machine learning paradigms such as inference on the edge. This integration will also generate and revitalize new research areas that encompass fundamental materials science to large-scale supply networking and cybersecurity to AI-enabled collaborative robotics and human-robot interaction and beyond. The activities also include new curriculum development both at the participating universities and community colleges, as well as plans for outreach through local governments and high schools, for developing the workforce for such a paradigm and broadening participation into AI-related technology among society.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.

先进制造业正处于第四次工业革命的风口浪尖，被称为工业4.0或智能制造。然而，在实现智能制造模式方面存在很多挑战。智能制造中设想的快速可重构生产系统本质上依赖于从车间的机器和自动化机器人以及分散在供应物流链中的实体中使用异构传感器获取大量连续流数据。数据必须通过具有严格延迟和安全保证的无线信道传输，并结合实时分析，以实现精确的故障排除，协调和监控。不可避免的结论是，为了实现智能制造，需要制造技术、机器人技术和控制、5G等网络协议以及边缘推理等机器学习范式的紧密集成--事实上是跨层优化。实现这一愿景是本规划赠款所设想的研究所的目标。实现一个有效的研究所将需要先进制造、人工智能、传感、计算和传感方面的专家，以及与工业和联邦研究实验室的合作。这项规划补助金的主要活动旨在通过一系列活动发展这样一个团队。该研究所的知识堡垒是通过制造技术、5G等网络协议、机器人和控制以及边缘推理等机器学习范式的紧密集成和跨层优化来实现智能制造。这种整合还将产生和振兴新的研究领域，包括基础材料科学，大规模供应网络和网络安全，人工智能支持的协作机器人和人机交互等。这些活动还包括在参与的大学和社区学院制定新的课程，以及通过地方政府和高中进行推广的计划，为这样一个范式发展劳动力，并扩大对人工智能的参与-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

期刊论文数量（18）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Effect of contaminations on the acoustic emissions during wire and arc additive manufacturing of 316L stainless steel

DOI：
10.1016/j.addma.2021.102585
发表时间：
2021-12
期刊：
Additive Manufacturing
影响因子：
11
作者：
A. Ramalho;T. Santos;Ben Bevans;Z. Smoqi;Prahalada K. Rao;J. P. Oliveira
通讯作者：
A. Ramalho;T. Santos;Ben Bevans;Z. Smoqi;Prahalada K. Rao;J. P. Oliveira

In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learning

DOI：
10.1007/s10845-022-01977-2
发表时间：
2022-06
期刊：
Journal of Intelligent Manufacturing
影响因子：
8.3
作者：
A. Gaikwad;Tammy Chang;B. Giera;N. Watkins;S. Mukherjee;A. Pascall;D. Stobbe;Prahalada K. Rao
通讯作者：
A. Gaikwad;Tammy Chang;B. Giera;N. Watkins;S. Mukherjee;A. Pascall;D. Stobbe;Prahalada K. Rao

Adversarial attacks in consensus-based multi-agent reinforcement learning

DOI：
10.23919/acc50511.2021.9483080
发表时间：
2021-03
期刊：
2021 American Control Conference (ACC)
影响因子：
0
作者：
Martin Figura;K. Kosaraju;V. Gupta
通讯作者：
Martin Figura;K. Kosaraju;V. Gupta

Closed-loop Control of Meltpool Temperature in Directed Energy Deposition

DOI：
10.1016/j.matdes.2022.110508
发表时间：
2022-03
期刊：
Materials & Design
影响因子：
0
作者：
Z. Smoqi;Ben Bevans;A. Gaikwad;J. Craig;Alan Abul-Haj;B. Roeder;B. Macy;J. Shield;Prahalada K. Rao
通讯作者：
Z. Smoqi;Ben Bevans;A. Gaikwad;J. Craig;Alan Abul-Haj;B. Roeder;B. Macy;J. Shield;Prahalada K. Rao

A 3D Printing Hexacopter: Design and Demonstration

3D 打印六轴飞行器：设计与演示