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Principal component analysis and fuzzy embedded Taguchi approach for multi-response optimisation in machining of GFRP polyester composites: a case study

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  • Ankita Singh
  • Saurav Datta
  • Siba Sankar Mahapatra

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.

Suggested Citation

  • Ankita Singh & Saurav Datta & Siba Sankar Mahapatra, 2013. "Principal component analysis and fuzzy embedded Taguchi approach for multi-response optimisation in machining of GFRP polyester composites: a case study," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 14(2), pages 175-206.
    • Handle: RePEc:ids:ijisen:v:14:y:2013:i:2:p:175-206
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    Cited by:

    1. Dey, Suman & Reang, Narath Moni & Majumder, Arindam & Deb, Madhujit & Das, Pankaj Kumar, 2020. "A hybrid ANN-Fuzzy approach for optimization of engine operating parameters of a CI engine fueled with diesel-palm biodiesel-ethanol blend," Energy, Elsevier, vol. 202(C).

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