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Critical parts for defense, aerospace, and medical applications must be formally qualified prior to use. Currently, extensive empirical testing consisting of
The Advanced Manufacturing Data Infrastructure and Analytics (AMDIA) program will lay the groundwork for advanced data infrastructure and corresponding
The application of robotics in manufacturing is hindered by their lack of agility, including their large changeover times for new tasks/products and their
Currently there is a significant interest in using additively manufactured parts in high-performance applications. However, due to a lack of publicly available
Develop and deploy advances in measurement science that enable key dimensions of cybersecurity for smart manufacturing systems, services, and components.
FEMA Responders often face daunting challenges during search and rescue tasks in dangerous environments. As such, the concept of including robots as a part of
Approaches categorized as “artificial intelligence” (AI) are enabling significant advances in robotics. These include symbolic logic, Bayesian statistics, and
Part quality in additive manufacturing (AM) is highly dependent on the process control, but there is a lack of adequate AM control methods and standards. In
The lack of repeatable process outcomes from additive manufacturing (AM) has been broadly acknowledged as an impediment to widespread implementation. While most
This program addresses measurements and standards necessary to develop and deploy advances in measurement science that will enable rapid design-to-product
To develop and deploy measurement science, standards, and test methods that advance manufacturing robotic system performance, collaboration, agility, autonomy
Multi-physics models are necessary to simulate, study, and optimize metal additive manufacturing (AM) processes, such as powder bed fusion (PBF) and directed
Part quality in additive manufacturing (AM) is highly variable due to inadequate dimensional tolerances, surface roughness, and defects, thereby limiting its
Mobile robots are expanding their capabilities well beyond the traditional role of Automatic/Automated/Autonomous Guided Vehicles (A-UGV) as they attain greater
Building on a successful first-year Strategic and Emerging Research Initiatives (SERI) project NIST and Autonomous Vehicles (see 2022 NIST AV workshop and
Sensors and algorithms are essential elements of any robotic system that is meant to be safe, adaptive, and productive in manufacturing environments. In the
Most manufacturing assembly tasks are not readily automatable today due to robots’ limited perception, mobility, and dexterity. The challenge of engineering and
The widespread use of robots in flexible factories (i.e., factory environments subject to high product turnover, short production runs, and high variability in
In terms of collaborative robotics, the widespread adoption of robots in historically manual manufacturing environments (which are subject to high product
The lack of repeatable process outcomes from additive manufacturing (AM) has been broadly acknowledged as an impediment to widespread implementation. While most