软件导刊2024，Vol.23Issue(1)：122-127,6.DOI:10.11907/rjdk.222482
基于贝叶斯理论的HotellingT2小样本多元工序质量监控方法
HotellingT2 Small Sample Multivariate Process Quality Monitoring Method Based on Bayesian Theory
摘要
Abstract
Traditional Hotelling T2 control chart method suitable for multivariate quality control has certain limitations in small batch process-ing due to its sensitivity to outliers due to limited sample data.To this end,Bayesian theory is combined with traditional Hotelling T2 control charts to estimate Bayesian parameters through historical batch process quality distribution information and existing real-time sample data.A Hotelling T2 process quality control chart based on Bayesian theory is constructed to resist the impact of outliers in the multivariate quality con-trol process of small batch processing.The analysis of quality control examples for engine camshaft processes shows that the proposed method can effectively resist the impact of outliers compared to traditional methods,has good anti-interference and stability,and can better monitor the uncontrolled state of process quality control.关键词
多元质量控制/贝叶斯理论/HotellingT2控制图Key words
multivariate quality control/Bayesian theory/HotellingT2 control chart分类
计算机与自动化引用本文复制引用
宁方华,骞文成,屠震元,陈智峰..基于贝叶斯理论的HotellingT2小样本多元工序质量监控方法[J].软件导刊,2024,23(1):122-127,6.基金项目
国家自然科学基金项目(51475434) （51475434）
浙江省2023年度"尖兵""领雁"研发攻关计划项目(2022C01SA111123) （2022C01SA111123）
