Title: Principal component analysis and fuzzy embedded Taguchi approach for multi-response optimisation in machining of GFRP polyester composites: a case study
Authors: Ankita Singh; Saurav Datta; Siba Sankar Mahapatra
Addresses: Department of Mechanical Engineering, National Institute of Technology, Rourkela 769008, Orissa, India ' Department of Mechanical Engineering, National Institute of Technology, Rourkela 769008, Orissa, India ' Department of Mechanical Engineering, National Institute of Technology, Rourkela 769008, Orissa, India
Abstract: This paper proposes an extended multi-objective optimisation philosophy applied in a case study of machining (turning) of randomly oriented glass fibre-reinforced plastic polyester composites. Design of experiment has been selected based on Taguchi's L9 orthogonal array design with varying process control parameters, such as spindle speed, feed rate and depth of cut. Multiple surface roughness parameters of the machined fibre-reinforced polymer product along with material removal rate of the machining process have been optimised simultaneously. A principal component analysis coupled with fuzzy inference system has been proposed for providing feasible means for meaningful aggregation of multiple objective functions into an equivalent single performance index. This multi-performance characteristic index has been optimised using Taguchi method.
Keywords: FRP; fibre reinforced polymer composites; PCA; principal component analysis; FIS; fuzzy inference systems; MPCI; multi-performance characteristic index; Taguchi methods; composites machining; GFRP composites; turning; glass fibre reinforced polymer; design of experiments; orthogonal arrays; process control; spindle speed; feed rate; depth of cut; surface roughness; surface quality; material removal rate; MRR.
DOI: 10.1504/IJISE.2013.053736
International Journal of Industrial and Systems Engineering, 2013 Vol.14 No.2, pp.175 - 206
Published online: 27 Dec 2013 *
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