DocumentCode
145758
Title
Data-driven development and maintenance of soft-sensors
Author
Abonyi, Janos ; Farsang, Barbara ; Kulcsar, Tibor
Author_Institution
Dept. of Process Eng., Univ. of Pannonia, Veszprem, Hungary
fYear
2014
fDate
23-25 Jan. 2014
Firstpage
239
Lastpage
244
Abstract
Product quality related process variables have significant role in advanced process control (APC). Online analyzers and software sensors can provide accurate and timely information for APC systems. In this paper we give an overview of data based soft-sensor development. We show that soft-sensor models of APC require maintenance and demonstrate that statistical quality control (SQC) techniques can be effectively used to automatize the related fault detection tasks.
Keywords
process control; quality control; sensors; APC systems; SQC technique; advanced process control; data-driven development; fault detection tasks; soft-sensor development; software sensors; statistical quality control technique; Data models; Maintenance engineering; Mathematical model; Principal component analysis; Process control; Quality assessment; Sensors;
fLanguage
English
Publisher
ieee
Conference_Titel
Applied Machine Intelligence and Informatics (SAMI), 2014 IEEE 12th International Symposium on
Conference_Location
Herl´any
Print_ISBN
978-1-4799-3441-6
Type
conf
DOI
10.1109/SAMI.2014.6822414
Filename
6822414
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