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At the 2023 INFORMS Annual Meeting , NIST researcher Mehdi Dadfarnia presented research findings based on use of NIST-developed SimPROCESD software, which can
CTL’s Smart Connected Manufacturing Systems Group and the Longterm Archiving and Retrieval (LOTAR) Consortium have supported multi-year efforts to harmonize
To provide the necessary information for electronic material manufacturers to predict how and when failures will occur and enable lifetime analysis appropriate
This project develops and applies metrologies and standards for characterizing microstructure and dynamics in advanced functional materials of technological
Part quality in additive manufacturing (AM) is highly variable due to inadequate dimensional tolerances, surface roughness, and defects, thereby limiting its
As part of the NIST on a Chip program, the Photonic Dosimetry project is developing in-situ sub-micrometer ionizing-radiation dosimetry and calorimetry leading
Manufacturers perpetually adapt their systems to meet unforeseen events, new objectives, competition, and improved understanding of processes. In that human
Lean manufacturing is based on data collection and analysis that is used toward reducing waste and enabling continuous improvement. However, little research has
Due to self-occlusions in 3D point clouds acquired with line-of-sight sensors, an incomplete representation of an object's surface is used in fitting a CAD
SimPROCESD is a discrete event simulation package written in Python that is designed to model the behavior of discrete manufacturing systems. Specifically, it
The Unit Manufacturing Process (UMP) Builder allows researchers to record their UMP models according to the ASTM E3012-16 standard .
One of the main drivers
Simantha is a discrete event simulation package written in Python that is designed to model the behavior of discrete manufacturing systems. Specifically, it