[1]夏蓓鑫,简铮,高雅,等.多变量过程监控的D控制图[J].华侨大学学报(自然科学版),2018,39(6):920-925.[doi:10.11830/ISSN.1000-5013.201707056]
　XIA Beixin,JIAN Zheng,GAO Ya,et al.D Control Chart for Multivariable Process Monitoring[J].Journal of Huaqiao University(Natural Science),2018,39(6):920-925.[doi:10.11830/ISSN.1000-5013.201707056]
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多变量过程监控的D控制图()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第39卷
期数:
2018年第6期
页码:
920-925
栏目:
出版日期:
2018-11-20

文章信息/Info

Title:
D Control Chart for Multivariable Process Monitoring
文章编号:
1000-5013(2018)06-0920-06
作者:
夏蓓鑫1;  简铮2;  高雅2;  陶宁蓉3
1. 上海大学 管理学院, 上海 200444;2. 上海大学 机电工程与自动化学院, 上海 200072;3. 上海海洋大学 工程学院, 上海 201306
Author(s):
XIA Beixin1;  JIAN Zheng2;  GAO Ya2;  TAO Ningrong3
1. School of Management, Shanghai University, Shanghai 200444, China; 2. School of Mechatronics Engineering and Automation, Shanghai University, Shanghai 200072, China; 3. College of Engineering, Shanghai Ocean University, Shanghai 201306, China
关键词:
D控制图;  多元统计过程控制;  支持向量数据描述;  平均运行链长
Keywords:
D control chart;  multivariate statistical process control;  support vector data description;  average run length
分类号:
TP206.3;O213.1
DOI:
10.11830/ISSN.1000-5013.201707056
文献标志码:
A
摘要:
针对如何将大数据技术与传统的多元控制图相结合,以获得一个具有自学习性的控制图的问题,以支持向量数据描述(SVDD)为构建基础,提出一个基于支持向量数据描述的D控制图.该D控制图通过对在控数据的学习,自适应地构建出自己的监控模型.仿真实验及工业实例表明:D控制图在多变量制造过程中的表现优于T2控制图,是一个理想的监控模型.
Abstract:
For the issue of how to combine the big data technology with the traditional multivariate control chart to get a control chart with self-learning. Based on support vector data description(SVDD), a D control chart with SVDD is proposed in this paper. The D control chart can adaptively construct its own monitoring model through being trained by the in-control data. Simulation results and industrial examples show that the D control chart has a better performance compared with the T2 control chart for the multivariable manufacturing process, and it is a promising monitoring model.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2017-07-22
通信作者: 夏蓓鑫(1984-),男,讲师,博士,主要从事质量管理、可靠性工程的研究.E-mail:bxxia@shu.edu.cn.
基金项目: 国家自然科学基金资助项目(71401098); 上海市高校青年教师培养资助计划(ZZSD15047)
更新日期/Last Update: 2018-11-20