Title :
Manufacturing flexibility measurement: a fuzzy logic framework
Author :
Tsourveloudis, Nikos C. ; Phillis, Yannis A.
Author_Institution :
Tech. Univ. of Crete, Chania, Greece
fDate :
8/1/1998 12:00:00 AM
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;
Journal_Title :
Robotics and Automation, IEEE Transactions on