Author(s)

A. F. Batzias & F.A. Batzias

Abstract

Computational and experimental process control by combining neurofuzzy approximation with multicriteria optimization A.F. Batzias and F.A. Batzias Department of Industrial Management and Technology, University of Piraeus, Greece. Abstract In this work we have designed / developed I implemented an algorithmic procedure for computational and experimental process control aiming to find out the optimal combination of industrial production conditions that satisfy specifications of a product set by a client or the market. For this purpose, a Transformation Mechanism (TM) is established which produces a mapping of processing conditions on product qualities by neurofuzzy approximation; TM is coupled with the inverse procedure (ITM) which connects a product quality vector with all possible combinations of production condition vectors. The clustering I filtering of these combinations gives the alternatives among which a fuzzy multicriteria method selects the best. Implementation with data provided by t

Keywords