The potential benefits of the Center research are significant and expansive. Improvements in re-usability, extensibility, interoperability and maintainability of solutions will improve manufacturing throughput and quality and reduce cost directly. Key DT framework capabilities such as virtual commissioning will facilitate faster and lower-cost ramp-up. A common framework will allow the benefits to extend to the entire manufacturing ecosystem and will enhance capabilities such as security and customer responsiveness. Lastly the Center will promote workforce development and empowerment by establishing environments and solutions for training, benchmarking and collaboration between competitors, suppliers, and customers in a technical, pre-competitive forum.
Digital Twins (DTs) have become pervasive in the manufacturing industry. Here we adopt the DT definition of [Moyne et al.], that a digital twin is some level of purpose-driven replica of a real thing (the physical twin) and is synchronized with its physical twin (equipment, component, process, product, etc.). Leveraging historical and real-time data, as well as data-driven and first-principles models, DTs in disparate forms have been used to solve manufacturing problems such as predictive maintenance and model-based process control. They have the potential to increase productivity and reduce costs, by reducing unscheduled downtime, increasing yield (reducing scrap), optimizing the supply-chain manufacturing ecosystem, and even facilitating reconfiguration of assets for rapid, low-cost virtual commissioning.
DT solutions have typically been developed in silos, which creates a strain on workforce, solution upkeep and maintenance, security, sustainability. A common DT framework and approach has the potential to significantly reduce demands on workforce expertise, improve productivity through cross-training and re-use of existing solutions, streamline maintenance, and improve security and sustainability.
The Proposed Center will bring together a group of industry partners and academics for collaborative research to develop DTs across a common framework to help improve manufacturing solutions.
Timeline for the Center:
Jan. 2023: Proposal for an IUCRC Planning Grant, with “letters of interest” from 20+ companies.
Sept. 2023: Planning Grant awarded.
Oct.-Dec. 2023: Discussions with key potential industry partners
Jan.8-9 2024: Workshop with industry partners. Collect letters of commitment,
June 2024: Submit full proposal, including “letters of commitment” from companies
June 2025: NSF Award for the Center!
July 2025: Center meeting (July 23, in Michigan and on Zoom)
Oct. 2025: Center Kick-off in Arizona (Oct. 9-10, on campus at ASU)
Jan. 2026: Center Research Projects Begin
Center Leadership
Ronald D. and Regina C. McNeil Department Chair of Robotics
University of Michigan
tilbury@umich.edu
Research Scientist
University of Michigan
moyne@umich.edu
Associate Professor, School of Manufacturing Systems and Networks
Ira A. Fulton Schools of Engineering, Arizona State University
Wenlong.Zhang@asu.edu
Associate Professor, School of Computing and Augmented Intelligence
Ira A. Fulton Schools of Engineering, Arizona State University
Giulia.Pedrielli@asu.edu
School Director and Professor, School of Manufacturing Systems and Networks
Ira A. Fulton Schools of Engineering, Arizona State University
Binil.Starly@asu.edu
A National Science Foundation (NSF) Industry-University Cooperative Research Center (IUCRC) is developed around emerging research topics of current research interest, in a pre-competitive space but with clear pathways to applied research and commercial development. NSF supports the administration and operation of IUCRCs. Industry partners support the research projects through their membership dues and choose the specific research projects that the center will execute.