Generative Learning for Simulation of Vehicle Faults
Kuiper, Patrick, Lin, Sirui, Blanchet, Jose, Tarokh, Vahid
We focus this analysis on the United States' Department of Defense (DoD), where the US Army alone is projected to spend an estimated $5 billion per year (in 2020 dollar terms through 2050), developing and acquiring ground vehicles, where ground vehicles are any vehicles other than aircraft and ships (CBO 2021). Maintaining this enormous investment is critical to ensuring combat readiness across the DoD, where the department spent $90 billion in 2022 on maintaining vehicles across domains: ground, air, and sea (GAO 2022). Predicting requirements is critical to an effective maintenance program. The application of statistics towards vehicle maintenance prediction is often referred to as predictive maintenance. Recognizing the importance of predictive maintenance, in the 2022 National Defense Authorization Act (NDAA) Congress required the DoD Inspector General Office to review predictive maintenance practices, originally established by DoD directives in 2002 and 2007 (DoDIG 2023).
Jul-30-2024
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- Personal (0.46)
- Research Report (0.64)
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- Technology:
- Information Technology
- Artificial Intelligence > Machine Learning
- Neural Networks (0.95)
- Performance Analysis > Accuracy (0.95)
- Statistical Learning (1.00)
- Data Science > Data Mining (1.00)
- Artificial Intelligence > Machine Learning
- Information Technology