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Forecasting Return on Investment (ROI) for Naval Aviation Maintenance Safety Initiatives
Technical Paper
2000-01-2094
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
The Maintenance Extension of the Human Factors Analysis and Classification System (HFACS-ME) was employed to categorize errors present in 470 FY 90-97 Naval Aviation Maintenance Related Mishaps (MRMs). HFACS-ME identified common error types present in MRMs: maintenance supervision, crew coordination, maintainer error, and procedural violations. The data derived from classifying maintenance errors was used to develop mathematical models that were then employed to generate notional cost estimates associated with them. These models were then used to forecast the potential impact of maintenance error interventions. Collectively, the taxonomic analysis and model development served to identify common maintenance error forms, and consequently the optimal targets that have the most potential return on investment (ROI). An analysis of potential ROI tied to human error interventions revealed that reducing error as little as 10% can result in saving critical assets, lives, and millions of dollars each year.
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Authors
Citation
Schmidt, J., Schmorrow, D., and Figlock, R., "Forecasting Return on Investment (ROI) for Naval Aviation Maintenance Safety Initiatives," SAE Technical Paper 2000-01-2094, 2000, https://doi.org/10.4271/2000-01-2094.Also In
References
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