Intelligent system for process quality assessment in steel coating lines with high current rectifiers

Author

de Abajo, N. ; Diaz, Gabriel

Author_Institution

Dept. of Electr. Eng., Oviedo Univ., Asturias, Spain

Volume

1

fYear

2005

fDate

2-6 Oct. 2005

Firstpage

543

Abstract

Quality assurance of final products is one of the main targets of every manufacturing industry. In achieving this aim, the steel sector is devoting great efforts in terms of I-R&D to apply new methodologies for process modeling and pattern recognition that are being widely used in other emergent areas of knowledge reporting great results. In line with these approaches, this work presents the deployment of some of these AI techniques in the identification of electrical failures in an industrial electrolytic process by means of analyzing the impacts that these failures have in the final product quality.

Keywords

data mining; electrolysis; electrolytic rectifiers; manufacturing processes; pattern recognition; quality assurance; steel industry; current rectifiers; data mining; electrical failures; electrolytic tinning lines; industrial electrolytic process; intelligent system; manufacturing industry; pattern recognition; process quality assessment; quality assurance; steel coating lines; Artificial intelligence; Coatings; Intelligent manufacturing systems; Intelligent systems; Manufacturing industries; Pattern recognition; Quality assessment; Quality assurance; Rectifiers; Steel;

fLanguage

English

Publisher

ieee

Conference_Titel

Industry Applications Conference, 2005. Fourtieth IAS Annual Meeting. Conference Record of the 2005

ISSN

0197-2618

Print_ISBN

0-7803-9208-6

Type

conf

DOI

10.1109/IAS.2005.1518360

Filename

1518360