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

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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.