Fuzzy process modelling for secondary steelmaking

Author

Roy, Rajkumar ; Collantes, L. ; Berdou, J. ; Whittaker, Harvey ; Madill, John

Author_Institution

Dept. of Enterprise Integration, Cranfield Univ., Milton Keynes, UK

fYear

1999

fDate

36342

Firstpage

864

Lastpage

868

Abstract

The application of artificial intelligence techniques in secondary steelmaking has been investigated by developing a prototype fuzzy process model. The fuzzy model assesses the quality of production using processing parameters as inputs and performance parameters as outputs, in order to provide an efficient decision support application. The research has developed an approach to utilise both data analysis and expert knowledge to define the membership functions and the rules. The paper also includes a brief state of the art review on the application of fuzzy logic in secondary steelmaking

Keywords

decision support systems; expert systems; fuzzy logic; fuzzy set theory; steel industry; steel manufacture; artificial intelligence techniques; data analysis; decision support application; expert knowledge; fuzzy logic; fuzzy process modelling; membership functions; performance parameters; processing parameters; production quality; prototype fuzzy process model; secondary steelmaking; Aluminum; Casting; Hydrogen; Iron alloys; Oxidation; Oxygen; Prototypes; Slag; Steel; Temperature control;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society, 1999. NAFIPS. 18th International Conference of the North American

Conference_Location

New York, NY

Print_ISBN

0-7803-5211-4

Type

conf

DOI

10.1109/NAFIPS.1999.781817

Filename

781817