Decisions are made every day about medical procedures such as surgeries or drug treatments: they affect and condition the future of patients. They are based on established best practices, but do not necessarily account for the individual traits of a person. A similar decision-making process can be found in complex engineering systems, or the maintenance schedule of an aircraft. During the last decade however,it has been recognized that the transition to personalized medicine will potentially enhance the life of patients and increase the quality of clinical care, as well as potentially lower the overall healthcare costs. A similar observation has been made regarding complex engineering systems, with a call to develop cyber-physical systems and dynamic data processes that use massive amounts of data to drive individual smart machines. The practical realization of this transition requires 1) the development of a new technology for extracting meaningful information from data and interpreting it correctly, 2) an accompanying plan for educating the future workforce in this global area, and 3) the identification and resolution of the associated ethical and privacy issues. This planning grant will develop the vision for the proposed Center to influence this transformation during the next two decades by influencing the health monitoring and decision-making processes of living and non-living physical entities in these important areas using digital twins. These are digital replicas of living and non-living physical entities. Their underlying concept integrates artificial intelligence, machine learning, and software analytics with physics-based modeling. Their main purpose is to act as living digital simulation models that are continuously trained and updated to be able to mirror the states and behaviors of their physical counterparts.
This grant will focus on planning the development of a Center that will integrate research groups working on core technologies for digital twins, such as algorithms, hardware, software,physics-based machine learning, and mathematics and statistics, with counterparts working on three significantly different application areas: aircraft health monitoring; customized weight loss programs; and qualification of metal 3D printed parts. This integration will define the common requirements for digital twins, advance these application areas and explore their societal and ethical implications. This will establish a multi-disciplinary dialog between mathematicians, engineers, medical doctors, lawyers and philosophers, and a convergent vision for how to shape the future of this technology. The grant will enable an Exploratory Workshop that will serve to identify the broad stakeholder community in academia and the corporate world and government, form the team and management structure, and most importantly, define a multi-disciplinary, convergent vision for a future Engineering Research Center in Digital Twins for Engineering and Medicine. The dialog that this planning grant will foster on the subjects of digital twins, engineering workforce development, diversity and culture of inclusion, and innovation ecosystem will build new connections between a diverse group of researchers and practitioners from different institutions and disciplines and identify the potential members of the Center. Additionally, explicit efforts are planned to engage partners from institutions that serve primarily underrepresented minorities in the activities of this planning grant. The impact of the newly formed connections with a shared interest in digital twins, in line with the idea of fostering a convergent research, has the potential to spring other areas of collaboration in the future.
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.
