摘要
传统的民用飞机装配质量问题处置主要依赖人工经验,通过借助大数据分析与人工智能技术能够有效提高装配效率与质量。本文选取中国商飞公司作为典型案例,分析基于文本挖掘的飞机装配质量问题智能诊断研究的实施过程,总结技术创新的具体实现路径。首先识别民机生产过程中质量管理的实际需求。然后借助大数据和人工智能相关技术,将非结构化文本信息转化为结构化数据,充分挖掘历史数据中的有效信息。最后以此为基础设计修复方案推荐算法,实现对质量问题的分析与处置,从而辅助人工进行管理决策,实现民机装配的提质增效。
Traditional disposition of civil aircraft assembly quality problems relies on human experience,and big data analysis and artificial intelligence technology can help to improve assembly efficiency and quality.COMAC was selected as a typical case to analyze the process of implementing intelligent diagnosis on aircraft assembly quality problems based on text mining,and to summarize the concrete realization path of technological innovation.First,the actual demand for the process of quality management was identified.Then,with the help of big data and artificial intelligence technology,the unstructured texts were transferred to structured data to mine valid information in historical data.Finally,an algorithm of the recommended repair solution was designed to analyze and dispose the quality problem.The application of this technology can assist artificial to make decisions and achieve the dual improvement of both efficiency and quality.
作者
袁博
郝澜宇
陈震
潘尔顺
YUAN Bo;HAO Lanyu;CHEN Zhen;PAN Ershun(School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China)
出处
《工业工程与管理》
北大核心
2021年第5期195-202,共8页
Industrial Engineering and Management
基金
中国商用飞机系统工程科技创新中心基金,国家自然科学基金(71672109)。
关键词
民机装配
文本挖掘
人工智能
辅助决策
质量问题
civil aircraft assembly
text mining
artificial intelligence
aided decision-making
quality problem
