Forecasting Return on Investment (ROI) for Naval Aviation Maintenance Safety Initiatives 2000-01-2094
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.
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. Download Citation
Author(s):
John Schmidt, Dylan Schmorrow, Robert Figlock
Affiliated:
Naval Postgraduate School, USN
Pages: 6
Event:
Advances In Aviation Safety Conference & Exposition
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Mathematical models
Human factors
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