Title :
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
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;
Conference_Titel :
Industry Applications Conference, 2005. Fourtieth IAS Annual Meeting. Conference Record of the 2005
Print_ISBN :
0-7803-9208-6
DOI :
10.1109/IAS.2005.1518360
