Application of genetically-generated fuzzy knowledge bases in manufacturing

Author

Balazinski, Marek ; Achiche, Sofiane ; Baron, Luc

Author_Institution

Dept. de Genie Mecanique, Ecole Polytech. de Montreal, Que., Canada

Volume

4

fYear

2001

fDate

25-28 July 2001

Firstpage

2023

Abstract

The need of an expert to build the knowledge base (KB) of fuzzy decision support systems (FDSS) is a strong limitation to the expansion of their use in industry. However, this paper presents a genetic algorithm (GA) capable of automatically building KBs from a set of sampled data. The GA produces a KB allowing an optimal approximation of a set of sampled data from a low amount of input information. The GA is validated with a theoretical surface and applied to a tool wear monitoring problem

Keywords

condition monitoring; fuzzy logic; genetic algorithms; knowledge based systems; machine tools; manufacturing data processing; compositional rule of inference; fuzzy decision support systems; fuzzy logic; genetic algorithm; genetically-generated fuzzy knowledge bases; knowledge base; manufacturing; tool wear monitoring; Decision support systems; Fuzzy logic; Fuzzy sets; Fuzzy systems; Genetic algorithms; Gravity; Knowledge based systems; Manufacturing; Monitoring; Optimization methods;

fLanguage

English

Publisher

ieee

Conference_Titel

IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th

Conference_Location

Vancouver, BC

Print_ISBN

0-7803-7078-3

Type

conf

DOI

10.1109/NAFIPS.2001.944379

Filename

944379