Abstract：The discrete manufacturing process of aerospace products, characterized by intricate assembly procedures, complex manufacturing techniques, and frequent technical status changes, brings a series of challenges for data management, especially difficulties in integrating multi-source heterogeneous data and inaccuracies in product status detection. To overcome these challenges, this paper has proposed a normalized automated product quality analysis process using multi-source, multi-modal data. Utilizing bill of material (BOM) as the data organization framework, leveraging data platform components enables real-time monitoring and early warning of product quality status across multiple batches via successful envelope analysis of single indicators and joint analysis of multiple indicators, thus allowing product quality and consistency to be enhanced precisely. This study provides theoretical support for the prediction and controlling of product qualities and offers guidance for subsequent quality analysis and reinspection.
吕弢, 陈璟, 薛善烨. 离散制造中基于多源多模数据的产品指标联合[J]. 空天防御, 2024, 7(5): 110-119.
LYU Tao, CHEN Jing, XUE Shanye. Joint Analysis of Product Indicators Based on Multi-Source and Multi-Modal Data in Discrete Manufacturing. Air & Space Defense, 2024, 7(5): 110-119.
