Title: TSK-type fuzzy rule based modelling of machining on MMCs

Authors: Arup Kumar Nandi

Addresses: Department of General Engineering Design, Central Mechanical Engineering Research Institute, MG Avenue, Durgapur-713209, West Bengal, India

Abstract: A combined approach of a Genetic Algorithm (GA) and Multiple Linear Regression (MLR) is proposed to construct the Knowledge Base (KB) of Fuzzy Rule Based Model (FRBM) for turning operations on Metal Matrix Composites (MMCs). The appropriate FRBM is arrived at after a thorough investigation of the performances of various FRBMs (constructed with different structures of Rule-Consequent Function (RCF)) by comparing their results with experimental data and existing correlation models, as well as by using statistical analysis. It has been shown that the structure of the RCF is a critical aspect for constructing appropriate TSK-type FRBMs for the concerned process.

Keywords: FRBM; fuzzy rule based modelling; TSK-type fuzzy rules; machining; turning; MMC; metal matrix composites; power requirements; GAs; genetic algorithms; MLR; multiple linear regression; ANOVA; t-test.

DOI: 10.1504/IJMMS.2010.029878

International Journal of Mechatronics and Manufacturing Systems, 2010 Vol.3 No.1/2, pp.116 - 130

Available online: 02 Dec 2009 *

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