基于人工智能的决策系统,用于飞机产品组装的工具设计,并开发了知识检索算法
Md Helal Miah1,2,3, Shashi Kant Gupta1,4, Lu Yali2
1Lincoln University College, Selangor Darul Ehsan, 47301, Petaling Jaya, Malaysia.
Scientific reports
|February 9, 2026
概括
这项研究介绍了飞机机翼备件工具设计的基于本体学的系统,通过改进的搜索和可追溯性来增强决策. 开发的知识检索实践 (KRP) 系统实现了高精度,为复杂的任务提供了可解释的指导.
科学领域:
- 航空航天工程 航空航天工程
- 知识管理知识管理
- 人工智能的人工智能
背景情况:
- 飞机机翼备件工具设计是复杂的,需要有效地访问广泛的技术信息.
- 传统的信息检索方法往往无法为复杂的设计任务提供决策准备指导.
- 减少搜索力度和提高可追溯性对于有效的产品开发至关重要.
研究的目的:
- 为飞机机翼备件工具设计开发基于本体学的知识检索实践 (KRP) 系统.
- 通过减少搜索力度,改善可追溯性和提供决策准备指导来加强决策.
- 整合多个检索模式,以获得全面的知识访问.
主要方法:
- 正式化了一个域本体学和基于规则的工具设计约束.
- 开发了一个查询信息模型,将自然语言映射到机器可解释的意图.
- 编排了三个检索模式:基于本体学的语义 (OBS),基于规则的推理 (RBI) 和基于案例的推理实例 (CBRI).
- 将系统集成到一个具有产品开发管理 (PDM) /计算机辅助设计 (CAD) 兼容性的五层平台中.
主要成果:
- 实现了93.1%的平均任务级准确性,混合OBS+RBI+CBRI配置达到96.9%的可靠性.
- 在分级工具公司上,文档级准确度在98-99%之间.
- 在域-不可知应力测试中,与传统的检索方法相比,证明了一致的收益.
- 确定了每个检索模式的特定优势:概念查询的OBS,可计算方面的RBI和结构类比的CBRI.
结论:
- 开发的KRP平台为复杂的组装任务提供了可部署的解决方案,提供了可解释和决策准备的指导.
- 为不同的查询类型选择适当的检索策略提供了可操作的指导.
- 该研究建立了一个可重复的评估协议,为未来的航空航天知识管理研究和基准铺平了道路.
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