Quantitative analysis of uncertainty in field data and calibration method for estimating life distribution parameters

In this study, to quantitatively evaluate the uncertainty of data input, electronic data, and handwritten data were compared and analyzed. Specifically, failure data of aircraft hydraulic actuators were used for failure trend and pattern analysis, descriptive statistical analysis, statistical lifetime analysis, and Bayesian network (BN) analysis. The field data used in weapons system reliability analysis uses electronic data from the Defense Logistics Integrated Information System (DELIIS). However, several issues have been identified in the quality of electronic data. To obtain meaningful results from reliability analysis, efforts are needed to reduce uncertainty in data input and improve quality. The analysis revealed that the quality of the electronic data was approximately 69% compared to the handwritten data. To address this issue, an integrated model based on Bayes’ theorem was presented. The integrated model increased the level of reliability analysis results by calibrating the parameters of the life distribution by combining the advantages of the two data types. The presented model can be continuously supplemented through Bayesian updates and is expected to be applicable to other weapon systems for which handwritten data exists.