A Study on the Attributes of Weapon System Equipment Maintenance Data

A thorough analysis of the attributes of data is essential for constructing a lifecycle encompassing data collection, storage, processing, analysis, and utilization. When limited to national defense weapon systems, building a data lifecycle optimized for total life cycle management becomes a key methodology. It addresses critical issues such as ensuring operational readiness, efficient budget execution, and improving performance and quality. The foundation for these solutions lies in quantitative indicators, which are derived from data. Therefore, establishing a comprehensive data lifecycle for weapon systems is imperative. This study focuses on the primary data attributes identified during the implementation of defense logistics informatization projects(e.g., Logistics Big Data Collection and Analysis System Construction Project, 2021.12.9.), particularly in the domain of equipment maintenance. Five key data attributes were examined: field operational parameters, condition inspection data, industrial data, sensor data, and environmental data. The study provides a comprehensive overview of the definitions, data formats, and collection methods for these five types of data, emphasizing critical considerations for managing equipment maintenance data. By doing so, it aims to facilitate detailed task execution and practical application in constructing the data lifecycle for weapon system maintenance. Ultimately, this research is expected to support the practical use of equipment maintenance data and the establishment of a robust data lifecycle, enabling effective and evidence-based improvements in maintenance practices for national defense weapon systems.