일회성 무기체계의 필드 빅데이터 분석을 통한 신뢰도 예측 보정계수 추정

Abstract

Purpose: This study aimed at developing a model that can improve the accuracy of reliability prediction through guided missile field big data analysis.<BR>Methods: All the relevant operational and field maintenance data was collected by cooperating with the maintenance organization within the military. A data purification method was adopted to analyze the collected data. Omissions and missing data were processed by using the results of a parallel review that was conducted by examining the results of the consultation session with the missile operation expert and the quality data of the missile producer. The actual data was analyzed at the level of military repair parts, and the correction factor was calculated.<BR>Results: Since the correction factor analyzed in this study was calculated at the component level, it can be applied to correct the predicted failure rate of components calculated when developing new weapon system projects in the future. It is possible to improve the accuracy of the analysis results in the field of element development, which requires the failure rate of the component unit.<BR>Conclusion: In this study, the reliability of a guided missile in the operations and maintenance phase was analyzed through field big data analysis of the missile. Based on the results, the reliability predicted during the R&D phase was corrected, and a methodology (correction factor) was applied to reduce the reliability gap.