基于工厂信息的实时数据流分析与全过程质量监控  

Real-time data stream analysis and entire process quality monitoring based on plant information

作　　者：边小勇[1] 张晓龙[1] 余海[1] 

机构地区：[1]武汉科技大学计算机科学与技术学院,武汉430065

出　　处：《计算机应用》2012年第10期2935-2939,共5页journal of Computer Applications

基　　金：国家自然科学基金资助项目(60975031);湖北省自然科学基金重点项目(2009CDA034);武汉市学科带头人计划项目(201150530152)

摘　　要：针对某钢铁企业生产过程中的生产信息不畅通、产品质量无法追踪问题,开展了基于工厂信息(PI)的实时数据流分析与全过程质量监控方法的研究。着重研究了实时数据流分割和过程监控,提出基于统计质量控制(SQC)图和工序性能指标的统计监控方法,并开发了一个产品技术质量监控系统,应用结果表明基于PI的实时数据流分析与产品质量监控实现了企业对生产工序质量的监控,以及关键生产工艺的识别与改进。This paper proposed a solution to do research on real-time data stream analyzing and entire process quality tracing based on PI （ Plant information） in order to solve these problems that the production information was blocked and product quality was unable to be traced in the steel production. The proposed solution focused on real-time data stream partition and process monitoring, and presented statistical monitoring methods based on Statistical Quality Control （SQC） charts and process capability indices. Furthermore, a product technique and quality monitoring system was developed. The applied results indicate the implementation of real-time data stream analysis and product quality monitoring based on PI can efficiently monitor production process quality, the identification and improvement of key production technology as well.

关 键 词：生产信息数据 工厂信息数据库 实时数据流分割 统计质量控制图 工序质量监控 

分 类 号：TP392[自动化与计算机技术—计算机应用技术]