Predicting Asset Degradation with Data-Driven Models

Authors

Kurt R. Lamm, USAF
Justin D. Delorit, Air Force Institute of TechnologyFollow
Steven J. Schuldt, Air Force Institute of TechnologyFollow

Document Type

Article

Publication Date

9-2021

Abstract

Asset management databases are widely employed to help close the maintenance/sustainment gap and to more proactively identify potential risks. However, current data models often use population averages to make predictions, which can overlook individual asset performance over its lifespan. Recent research at the Air Force Institute of Technology investigated using stepwise asset condition forecast models to develop better predictions.

Comments

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DOI

JSTOR:48621912

Source Publication

The Military Engineer

Recommended Citation

Lamm, K., Delorit, J., & Schuldt, S. (2021). Predicting Asset Degradation with Data-Driven Models. The Military Engineer, 113(735), 62–63.