基于云模型与凝聚型层次聚类的失效模式与影响分析方法

Improving FMEA Based on Cloud Model and Hierarchical Agglomerative Clustering

摘要:

针对传统失效模式与影响分析（failure mode and effect analysis，FMEA）的不足，提出了一种基于云模型和凝聚型层次聚类算法的改进FMEA方法。首先，运用云模型对专家评估信息进行描述与集结；然后，结合凝聚型层次聚类算法识别云模型评价信息，利用聚类子簇确定失效模式间关联关系，利用聚类结果确定失效模式风险等级。最后，以在线教学失效风险评估为例，验证了该改进FMEA方法的可行性和有效性。

Abstract:

An improved FMEA method based on cloud model and agglomerated hierarchical clustering algorithm is proposed as to improve the RPN algorithm of failure mode and effect analysis （FMEA）. Firstly， the expert evaluation information is described and aggregated by the cloud model. Then， the cloud model is improved by the agglomerated hierarchical clustering algorithm， the correlation relationship among the failure modes is determined according to the clustering sub-clusters of the cloud model， and the risk level of the failure modes is determined according to the clustering results. Finally， the application and validity of the improved FMEA method are verified， by taking the online teaching failure risk assessment as an example.