Application issues of industrial soft computing systems

Author

Kordon, A.K.

Author_Institution

Dept. of Material Sci., Dow Chem. Co., Freeport, TX, USA

fYear

2005

fDate

26-28 June 2005

Firstpage

110

Lastpage

115

Abstract

An overview of the key technical, organizational, and political issues that need to be resolved for successful application of soft computing systems in industry is given in the paper. An integrated methodology with neural networks, support vector machines, and genetic programming is recommended. Several examples of successful soft computing applications in the chemical industry are given. The key explored application areas are inferential sensors, automated operating discipline, process emulators, accelerated new product development, and complex process optimization.

Keywords

fuzzy logic; genetic algorithms; industries; neural nets; organisational aspects; politics; support vector machines; uncertainty handling; accelerated new product development; automated operating discipline; complex process optimization; genetic programming; industrial soft computing systems; inferential sensors; neural networks; organizational issues; political issues; process emulators; support vector machines; technical issues; Acceleration; Chemical industry; Chemical sensors; Computer applications; Computer industry; Genetic programming; Machinery production industries; Neural networks; Product development; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society, 2005. NAFIPS 2005. Annual Meeting of the North American

Print_ISBN

0-7803-9187-X

Type

conf

DOI

10.1109/NAFIPS.2005.1548517

Filename

1548517