Manufacturing flexibility measurement: a fuzzy logic framework

Author

Tsourveloudis, Nikos C. ; Phillis, Yannis A.

Author_Institution

Tech. Univ. of Crete, Chania, Greece

Volume

14

Issue

4

fYear

1998

fDate

8/1/1998 12:00:00 AM

Firstpage

513

Lastpage

524

Abstract

Flexibility is recognized as an important feature in manufacturing. This paper suggests a knowledge-based methodology for the measurement of manufacturing flexibility. We claim that flexibility is an inherently vague notion and an essential requirement in its measurement is the involvement of human perception and belief. Nine different flexibility types are measured, while the overall flexibility is given as the combined effect of these types. Knowledge is represented via IF (fuzzy antecedents) THEN (fuzzy consequent) rules, which are used to model the functional dependencies between operational characteristics, such as setup time and cost, versatility, part variety, transfer speed, etc. The proposed scheme is illustrated through an example

Keywords

fuzzy logic; inference mechanisms; knowledge based systems; knowledge representation; manufacturing data processing; production control; approximate reasoning; flexibility measurement; fuzzy logic; if then rules; knowledge representation; knowledge-based systems; manufacturing; Cost function; Fuzzy logic; Fuzzy sets; Globalization; Humans; Multidimensional systems; Particle measurements; Production systems; Pulp manufacturing; Shape;

fLanguage

English

Journal_Title

Robotics and Automation, IEEE Transactions on

Publisher

ieee

ISSN

1042-296X

Type

jour

DOI

10.1109/70.704212

Filename

704212