一种面向多源业务数据的飞机质量数据挖掘与分析方法

A Method of Aircraft Quality Data Mining and Analysis for Multi-source Business Data

为提高对飞机质量数据分析的深度,笔者提出一种面向多源业务数据的质量数据挖掘和分析方法。该方法构建了面向多源异构业务系统数据分析应用的分层模型,以支撑运用数据挖掘算法分析质量关键因素之间的关系,并提出应用质量数据分析成熟度模型指导质量数据分析的层次。最后,笔者以某飞机制造企业某时间段的零件质量数据为例,基于产品层次运用关联规则算法挖掘设备因素与产品质量的关联关系,并结合专家领域知识对挖掘结果进行分析,能够为设备维修计划提供依据,验证了方法的有效性。

In order to improve the depth of aircraft quality data analysis,the author proposes a quality data mining and analysis method for multi-source business data.This method constructs a hierarchical model for data analysis application of multi-source heterogeneous business system to support the use of data mining algorithm to analyze the relationship between quality key factors,and proposes the application of quality data analysis maturity model to guide the level of quality data analysis.Finally,taking the part quality data of a certain period of time in an aircraft manufacturing enterprise as an example,based on the product level,the association rules algorithm is used to mine the association relationship between equipment factors and product quality,and the mining results are analyzed with the expert domain knowledge,which can provide the basis for equipment maintenance planning and verify the effectiveness of the method.