A Study on an ASRP Based Approach for Guided Missiles Considering Electronic Component Failure Characteristics
Year: 2026
Type: article
Abstract: Purpose: This study develops a system-level storage reliability management framework that explicitly integrates electronic components into the Ammunition Stockpile Reliability Program (ASRP). While conventional ASRP primarily focuses on the chemical degradation of propellants and explosives, the increasing reliance of modern missile systems on electronics-which exhibit random failure characteristics-requires an enhanced approach to ensure long-term mission readiness.Methods: The proposed framework integrates design reliability data from the production phase with operational periodic inspection data. Failure rate trends are analyzed to classify electronic components by failure characteristics, enabling the development of tailored management strategies. Furthermore, the Martinez-type inspection interval model is applied to determine optimal system-level inspection intervals and related management parameters.Results: The framework facilitates the dynamic adjustment of management intensity by comparing design failure rates with operational data to identify significant performance deviations. By utilizing the Martinez-type model, the study evaluates whether existing inspection cycles satisfy target storage reliability requirements and derives optimized intervals to maintain system integrity.Conclusion: This study provides a practical, data-driven extension of the ASRP and a systematic methodology for the storage reliability management of advanced missile systems. The proposed framework overcomes the limitations of existing degradation-centric models that overlook the random failure characteristics of electronic components and their weak correlation with storage time.
Institutions: Kyonggi University, Defense Agency for Technology and Quality
Language: English
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7166571339