Abstract & Details
Description
Award ID: 2333801
This project aims to prototype and deploy a Supply and Demand Open Knowledge Network (SUDOKN) that can serve as the knowledge base for supply chain analysis and risk management solutions in various industries, including defense, aerospace, automotive, and biomanufacturing. SUDOKN will consist of several open and interconnected knowledge graphs, built on various types of supply and demand data. These graphs will address challenges related to supplier discovery, capability, and capacity analysis, and will align with formal ontologies. This project will democratize access to publicly available supply and demand data and maximize its utility by developing a set of principle-based, accurately axiomatized, and reusable ontologies, creating the tools required to ingest, gather, process, and search manufacturing data, and utilizing these tools and ontologies to build an open Manufacturing Capability Network and its supporting knowledge graphs from diverse datasets. This research integrates concepts from a variety of disciplines, including philosophy, computer science, systems engineering, supply chain and logistics, and design and manufacturing engineering. The project advances the state-of-the-art in cyber-manufacturing by establishing a new formalism for manufacturing capability modeling. It creates an open ecosystem of manufacturing services aligned with the Manufacturing-as-a-Service (MaaS) paradigm and develops original methods and algorithms to provide manufacturing resources with cognitive capabilities. This effort aims to empower small and medium-sized manufacturers (SMMs) by enhancing their visibility, competitiveness, and agility. It will stimulate new research into understanding how manufacturing capabilities form and evolve over time. The results will contribute to more resilient and robust U.S. supply chains, directly impacting our national security and economic prosperity. The project outcomes will be integrated into the graduate and undergraduate curricula at the participating institutions, with students playing a direct role in this research agenda. 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.
NSF Program Director: Jemin George
This project aims to prototype and deploy a Supply and Demand Open Knowledge Network (SUDOKN) that can serve as the knowledge base for supply chain analysis and risk management solutions in various industries, including defense, aerospace, automotive, and biomanufacturing. SUDOKN will consist of several open and interconnected knowledge graphs, built on various types of supply and demand data. These graphs will address challenges related to supplier discovery, capability, and capacity analysis, and will align with formal ontologies. This project will democratize access to publicly available supply and demand data and maximize its utility by developing a set of principle-based, accurately axiomatized, and reusable ontologies, creating the tools required to ingest, gather, process, and search manufacturing data, and utilizing these tools and ontologies to build an open Manufacturing Capability Network and its supporting knowledge graphs from diverse datasets. This research integrates concepts from a variety of disciplines, including philosophy, computer science, systems engineering, supply chain and logistics, and design and manufacturing engineering. The project advances the state-of-the-art in cyber-manufacturing by establishing a new formalism for manufacturing capability modeling. It creates an open ecosystem of manufacturing services aligned with the Manufacturing-as-a-Service (MaaS) paradigm and develops original methods and algorithms to provide manufacturing resources with cognitive capabilities. This effort aims to empower small and medium-sized manufacturers (SMMs) by enhancing their visibility, competitiveness, and agility. It will stimulate new research into understanding how manufacturing capabilities form and evolve over time. The results will contribute to more resilient and robust U.S. supply chains, directly impacting our national security and economic prosperity. The project outcomes will be integrated into the graduate and undergraduate curricula at the participating institutions, with students playing a direct role in this research agenda. 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.
NSF Program Director: Jemin George
| Status | Active |
|---|---|
| Effective start/end date | 10/01/23 → 05/31/27 |
Funding
- (Proto-OKN) Prototype Open Knowledge Networks: $1,499,996.00
Active Fiscal Year
- FY2024
- FY2026
- FY2025
- FY2027
Start Fiscal Year
- FY2024
TIP Programs
- (Proto-OKN) Prototype Open Knowledge Networks
Key Technology Areas
- Artificial Intelligence
- (confidence score: 100%)
- Data and Cybersecurity
- (confidence score: 100%)
- Robotics and Advanced Manufacturing
- (confidence score: 100%)
Technology Foci
- Distributed Ledger Technologies
- (confidence score: 98%)
- Data Management / Databases
- (confidence score: 98%)
- Automation
- (confidence score: 97%)
- Machine Learning Training Data
- (confidence score: 88%)
- Artificial Intelligence (excluding ML)
- (confidence score: 96%)
Congressional District at Award
- District n. 01 of Arizona
Current Congressional District
- District n. 04 of Arizona
United States
- Arizona
Core Based Statistical Area (CBSA)
- Phoenix-Mesa-Chandler, AZ
County
- County: Maricopa, AZ
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