Multivariate Approach for Equipment Health Monitoring

被引：2
作者：
Krauel, Christopher [1 ]
Weishaeupl, Laura [1 ]
机构：
[1] Fraunhofer Inst Integrated Syst & Device Technol, Erlangen, Germany
来源：
IFAC PAPERSONLINE | 2016年 / 49卷 / 12期
关键词：
Monitoring; Equipment Health Factor; Semiconductor; Feature Selection; Condition Monitoring; FAULT-DETECTION; DIAGNOSIS;
D O I：
10.1016/j.ifacol.2016.07.858
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper deals with a method for equipment health monitoring through a multivariate approach. The approach concentrates on the autonomous classification of different process variable types which are defined by particular variable behaviors and the investigation of specified statistical feature extraction methods for every respective class. Also the computation of the equipment health factor (EHF) is presented. We provide a general method for detection of unknown failures through a multivariate approach to minimize production costs while still maintaining high yield. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码：716 / 720
页数：5
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