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Minimize RSR Award Detail

Research Spending & Results

Award Detail

Awardee:UNIVERSITY OF SOUTH CAROLINA
Doing Business As Name:University of South Carolina at Columbia
PD/PI:
  • Ramy Harik
  • (803) 777-7093
  • harik@cec.sc.edu
Co-PD(s)/co-PI(s):
  • Thorsten Wuest
Award Date:09/16/2021
Estimated Total Award Amount: $ 3,832,326
Funds Obligated to Date: $ 931,932
  • FY 2021=$931,932
Start Date:10/01/2021
End Date:09/30/2025
Transaction Type: Cooperative Agreements
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.083
Primary Program Source:040100 NSF RESEARCH & RELATED ACTIVIT
Award Title or Description:RII Track 2 FEC: Enabling Factory to Factory (F2F) Networking for Future Manufacturing
Federal Award ID Number:2119654
DUNS ID:041387846
Parent DUNS ID:041387846
Program:EPSCoR Research Infrastructure
Program Officer:
  • Eric Lindquist
  • (703) 292-7127
  • elindqui@nsf.gov

Awardee Location

Street:Sponsored Awards Management
City:COLUMBIA
State:SC
ZIP:29208-0001
County:Columbia
Country:US
Awardee Cong. District:06

Primary Place of Performance

Organization Name:University of South Carolina at Columbia
Street:
City:Columbia
State:SC
ZIP:29208-0001
County:Columbia
Country:US
Cong. District:06

Abstract at Time of Award

Cyber infrastructure and artificial intelligence (AI) are core components of smart manufacturing in South Carolina (SC), West Virginia (WV), and the United States. To drive radical transformation of industry, factories must securely expand beyond their physical boundaries. These Future Factories (FF) consume and create interdisciplinary knowledge along with the ability to forge innovative technological transformations. This project introduces a novel future cyber-manufacturing paradigm – the Factory-to-Factory (F2F) network framework. Geared towards automation, F2F networks require interoperability of stakeholders and efficient understanding systems for data, information, and knowledge. This collaboration between academia – led by the University of South Carolina and West Virginia University - and industry will produce advanced smart manufacturing technologies and an educated upskilled workforce in SC and WV. Furthermore, it will create a blueprint model for future manufacturing technologies that can be integrated with a F2F network to increase small-scale and industrial manufacturing capabilities across the US. To expand our workforce infrastructure, we will establish a lifelong learning pipeline for smart manufacturing ranging from K-12 education, higher education, to professional development support for scholars and industrial professionals. Particularly, we will create online learning resources and STEM-oriented smart manufacturing summer programs for K-12 students and provide internships for college and graduate students through our industrial partners. This project will adapt, enhance, and integrate informational technologies (IT) and operational technologies (OT) such as real-time secured sensing, high performance computing, wireless communications, and AI, to support process optimization among distributed smart manufacturing systems for F2F. Convergence and true progress can only be achieved by fusing expert knowledge of manufacturing processes with newly emerged hardware and software technologies. The project focuses on manufacturing knowledge stemming from: (1) autonomous feature extraction and recognition from product ‘manufacturing DNAs’ as a novel manufacturing knowledge representation among distributed systems, (2) architecture of interactive cyber spaces that combines cross-platform simulation results within product lifecycles, (3) data-driven control theories during process monitoring leading to rapid autonomous decision-making in replacement of manual input/output modules, and (4) robust business models and operations research (information service-oriented) concerning autonomous Key Performance Indicator (KPI) decomposition among distributed sub-systems and rapid feedback control loops. This will build a foundation for real-time production information sharing and control platforms and facilitate manufacturing knowledge generation and utilization among networked systems to address manufacturing management challenges. Furthermore, it enables human interventions and interoperations in the development and decision-making process of these highly collaborative networked smart manufacturing systems. This project will showcase several novel cyber manufacturing implementations and establish a roadmap towards a universal digital F2F standard. 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.

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