复杂产品关键质量特性识别方法

摘要

在复杂产品的关键质量特性(critical-to-quality characteristics,CTQ)识别中,传统方法应用于不平衡数据时会表现出有偏性,即对占类别比例较小的不合格产品识别的性能明显劣于占比例较大的合格样本.为解决以上问题,提出了基于改进信息增益( information gain,IG)算法的复杂产品高维不平衡数据集CTQ识别方法,利用改进IG算法评价标准降低不平衡数据中有偏性的影响,从而有效识别CTQ.算例结果表明该方法可以显著提高不平衡数据关键质量特性识别性能.%Often, most of products to be inspected are qualified, and only a small fraction is unqualified. In other words, the number of qualified and unqualified products are highly unbalanced. In the identification of critical-to-quality characteristics (CTQ) , significant performance deviation is observed when traditional method is applied. The performance of identifying CTQ for the unqualified products is significantly inferior to that for the qualified products. In order to solve problem, improved information gain (IG) algorithm is proposed to process such high-dimension imbalance data. By this method, it reduces the influence of imbalance data on the performance such that the identification of CTQ is significantly improved. Numerical simulation for an example verifies the effectiveness of the proposed method.