【摘要】 将IG(Information Gain)方法引入高维复杂产品质量特性识别,根据复杂产品制造过程的特点,将产品样本数据集中质量特性与样本质量类别建立联系,构建基于IG的相关性识别模型判别两者之间相关性及质量特性的有用性,从而去掉原始样本数据集中的弱相关特征及冗余特征,识别出对于产品质量具有直接关键影响的关键质量特性。算例结果表明,该方法可以比较有效消除在原始样本数据集中的冗余和不相关特征,适合用于高维复杂产品关键质量特性识别。更多还原

【Abstract】 The Information Gain(IG) Methodology is introduced into the identification of CTQ in the high dimensional complex products.According to the characteristics of the manufacturing process,the relationship between the quality characteristics and the class of each product sample is constructed.Then a model is structured based on IG methodology to identify the correlations between the mentioned two elements,and the service ability of the quality characteristics so as to remove the irrelevant and useless characteristics from the original sample dataset,and identify the CTQ,which have direct influence on the product quality.The experimental result indicates that the proposed methodology can eliminate the useless and irrelevant characteristics from the original dataset,and thus achieve the identification of the complex products’ CTQ effectively.更多还原