上海管理科学2025，Vol.47Issue(6)：18-22,5.
数据驱动的预测性质量管理综述
An Overview of Data-Driven Predictive Quality Management
摘要
Abstract
This paper aims to systematically elaborate on the core methods,key technologies,and implementation pathways of data-driven predictive quality management(PQM).Through a systematic review method,it analyzes the application mechanisms of multiple technologies,including artificial in-telligence,industrial Internet of Things,big data,and digital twins,in quality prediction,anomaly de-tection,and process optimization,and proposes a five-stage implementation pathway from data infra-structure construction to model iteration.The research results indicate that PQM can achieve a para-digm shift from"controlling variation"to"predicting the future,"significantly improving the accuracy and proactivity of quality management.关键词
预测性质量管理/人工智能/数字孪生/缺陷预测Key words
predictive quality management/artificial intelligence/digital twins/defect prediction分类
管理科学引用本文复制引用
尤建新,武小军..数据驱动的预测性质量管理综述[J].上海管理科学,2025,47(6):18-22,5.基金项目
国家社会科学基金重大项目(21ZDA024) （21ZDA024）
