摘要
为解决产品质量评估过多依赖专家经验,对测试过程指标数据利用和分析不足的问题,提出一种基于高斯混合模型的产品质量评估方法。首先,针对产品构建融合测试过程数据的质量评估指标集;然后基于质量评估指标集,提出一种基于随机森林和信息熵结合的评估指标重要度分析方法;最后构建基于高斯混合模型的质量评估模型,实现对产品质量的评估。通过对某企业半液浮速率陀螺仪装配质量的评估,表明该方法对企业实现产品质量差异化管理有着积极的作用。
In order to solve the problem that product quality evaluation relies too much on expert experience and insufficient utilization and analysis of test process index data,this paper proposes a product quality evaluation method based on Gaussian mixture model.Firstly,a set of quality assessment indicators is built for the product to fuse test process data.Then,based on the quality assessment index set,a method of assessment index importance analysis based on the combination of random forest and information entropy is proposed.Finally,a quality evaluation model based on Gaussian mixture model is constructed to evaluate product quality.The evaluation of the assembly quality of a company’s semi-liquid buoyancy rate gyroscope shows that this method has a positive effect on the company’s product quality differentiation management.
作者
常建涛
袁明坤
李欣伟
吴亮东
梁卫卫
CHANG Jian-tao;YUAN Ming-kun;LI Xin-wei;WU Liang-dong;LIANG Wei-wei(School of Mechano-Electronic Engineering,Xidian University,Xi'an 710071,China)
出处
《装备制造技术》
2020年第12期1-5,19,共6页
Equipment Manufacturing Technology
基金
“高档数控机床与基础制造装备”科技重大专项(2019ZX04025001)
“面向SMT产线的制造大数据耦合关联分析技术研究”陕西省重点研发计划(2020ZDLGY07-08)。
关键词
质量评估
指标重要度
随机森林
高斯混合模型
quality evaluation
index importance
random forest
gaussian mixture model