IUCRC Planning Grant University of Michigan: Center for Digital Twins for Consolidated Manufacturing Intelligence (DTCMI)

Regents Of The University Of Michigan - Ann Arbor, Ann Arbor MI

Investigators

Abstract

Digital Twins are purpose-driven software entities that collect run-time data from an operating manufacturing system, and bring that data together with models (representing both historical and theoretical behaviors) to create outputs and metrics that can be used to improve the overall performance of the manufacturing system. The development of Digital Twins requires significant subject matter expertise, where operators and engineers help determine the appropriate data to collect, modeling frameworks, and the most useful output metrics. This planning grant will build industry partnerships and develop a set of research directions in the area of Digital Twins for Consolidated Manufacturing Intelligence. Through a two-day workshop and multiple smaller conversations including the development of an industrial advisory board, industry partners will be engaged with university partners to develop a plan for a full IUCRC proposal. The resulting research directions have the potential to improve overall manufacturing operations, increasing productivity, leading to more profitability for manufacturers as well as lower costs and higher quality for consumers. The proposed center will engage both undergraduate and graduate students in the research projects, giving them experience in working on relevant industrial research projects. The research that will be proposed in the full IUCRC will relate to the development of methodologies and solutions for Digital Twins in the manufacturing industries. Given the primary site at the University of Michigan, automotive manufacturers and tier suppliers will be engaged as partners. As the system-level challenges are quite common across industries (even with very different processes), semiconductor fabrication and chemical process companies will also be engaged. A common framework for Digital Twins will be used to extend and reuse manufacturing intelligence and provide practical solutions to support evolution from reactive to predictive, proactive and prescriptive solutions envisioned in smart manufacturing and industry 4.0/5.0. Contributions will be in defining research directions that allow the framework and its elements to be re-useable, interoperable, extensible, and maintainable, but also in defining the state-of-the-art and deriving a research and development roadmap for key Digital Twin enabled solutions such as predictive maintenance and virtual commissioning. The planning activities will make use of the SMART 4.0 testbed in the Ford Robotics Building at the University of Michigan, that includes both additive and subtractive manufacturing processes, mobile and fixed-base collaborative robots, and an integrated data and control platform. 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.