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
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;
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
DOI :
10.1109/SAMI.2014.6822414
