ERI: Autonomous Digital Twinning of Manufacturing Systems Through Deep Learning-Enabled Co — NSF Award to Miami University (OH, $1
As manufacturing becomes increasingly digitized through cyber-physical systems and widespread industrial sensor deployment, digital twins (DTs) have emerged as critical tools for improving productivity, decision-making, and system optimization. These virtual representations of manufacturing assets enable real-time moni
| Award title | ERI: Autonomous Digital Twinning of Manufacturing Systems Through Deep Learning-Enabled Co |
|---|---|
| Award ID | 2501878 |
| Awardee | Miami University |
| City | OXFORD |
| State | OH |
| Amount obligated | $199,066 |
| Principal investigator | Clayton Cooper |
| Program | MSI-Manufacturing Systms Integ |
| Start date | 07/01/2025 |
| Abstract | As manufacturing becomes increasingly digitized through cyber-physical systems and widespread industrial sensor deployment, digital twins (DTs) have emerged as critical tools for improving productivity, decision-making, and system optimization. These virtual representations of manufacturing assets enable real-time monitoring, predictive maintenance, and process planning. However, constructing a DT of a manufacturing system remains a labor-intensive challenge, often requiring manual identificatio |
| Source | NSF Awards |
$799/mo
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