Fuzzy Approach to Measure Manufacturing Agility along with Developing Fuzzy Inference Systems in MATLAB

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Author(s) Ritu Chandna | S.R. Ansari
Pages 915-921
Volume 2
Issue 6
Date June, 2012
Keywords Agility, Fuzzy Inference System, Fuzzy logic, expert knowledge, Agility measurement


Agility is the ability of an organization to respond quickly and successfully to change. The integration of information system/technologies, people, business processes and facilities is the basis of an agile enterprise. Due to the ill-defined and vague indicators which exist within agility measurement, most measures are described subjectively by linguistic terms which are characterized by ambiguity and multi-possibility, and the conventional assessment approaches cannot suitably nor effectively handle such measurement. However, fuzzy logic provides a useful tool for dealing with decisions in which the phenomena are imprecise and vague. For measuring agility we use “IF (Fuzzy antecedents) THEN (Fuzzy consequent)” rules. In this paper, fuzzy inference systems (FIS) are designed, in several steps: fuzzification, aggregation of antecedents, inferencing, composition, and defuzzification. The key idea of our model in measurement is the involvement of all distinct dimensions and corresponding operational parameters in the determination of the overall agility. The proposed scheme is illustrated through an example.

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