Title :
Fuzzy assessment of machine flexibility
Author :
Tsourveloudis, Nikos C. ; Phillis, Yannis A.
Author_Institution :
Dept. of Production Eng. & Manage., Tech. Univ. of Crete, Chania, Greece
fDate :
2/1/1998 12:00:00 AM
Abstract :
Manufacturing flexibility is a difficult and multifaceted concept that because of its inherent complexity and fuzziness is amenable to an artificial intelligence treatment. Fuzzy logic offers a suitable framework for measuring flexibility in its various aspects. This paper deals with the measurement of machine flexibility. When data are precise, this is done via a simple analytical formula. But if such data, and hence knowledge, are not precise, fuzzy-logic modeling should be employed by transforming the human expertise into IF-THEN rules and membership functions. An implementation of the interval-valued fuzzy-set approach, together with a max-min schema, provides the approximate inference mechanism for the computation of machine flexibility. This approach has the advantage of revealing second-order semantic uncertainty with the associated nonspecificity measure. The models are illustrated with a number of examples
Keywords :
flexible manufacturing systems; fuzzy logic; fuzzy set theory; inference mechanisms; production; uncertainty handling; IF-THEN rules; approximate inference mechanism; approximate reasoning; artificial intelligence; associated nonspecificity measure; fuzzy assessment; fuzzy logic; fuzzy-logic modeling; interval-valued fuzzy-set approach; linguistic rules; machine flexibility measurement; manufacturing flexibility; max-min schema; membership functions; production system; second-order semantic uncertainty; Artificial intelligence; Associate members; Decision making; Engineering management; Fuzzy logic; Humans; Machinery production industries; Manufacturing; Production engineering; Production systems;
Journal_Title :
Engineering Management, IEEE Transactions on