Reliability Growth Analysis using Aircraft Operational Data for MTBF Prediction: An Exploratory Case Study

Purpose: This study evaluates the applicability of reliability growth slope-based extrapolation for predicting future MTBF using cumulative aircraft operational data.<br/>Methods: Operational data from a Republic of Korea Air Force aircraft, including cumulative flight hours and failure records, were analyzed using the Duane reliability growth model. Reliability growth slopes were estimated at 10,000, 30,000, and 50,000 flight-hour reference points using a sliding window approach. The estimated slopes were extrapolated to predict future MTBF values at later operational stages. Prediction accuracy was evaluated by comparing predicted and actual MTBF values using RMSE.<br/>Results: MTBF predictions based on early operational data showed relatively higher error rates.<br/>Prediction accuracy improved as cumulative operational data increased. These results indicate that reliability growth slope estimation is highly dependent on the sufficiency of operational data.<br/>Conclusion: This study demonstrates the applicability of reliability growth analysis using operational aircraft maintenance data. The results show that operational reliability data can support MTBF forecasting and logistics decision-making. Prediction accuracy improved as operational data accumulated over time. Future research should incorporate subsystem-level analysis and additional operational factors.