978-620-2-68041-7

OPTIMIZATION OF PARAMETERS FOR MILLING OF GFRP COMPOSITES

Modelling and Optimization of Process Parameters Using Taguchi and Fuzzy Logic in Milling of GFRP Composites

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Summary:

High quality surface milling of Fibre Reinforced Plastic (FRP) materials present a number of problems, such milling is one of the most frequently used material removal processes in machining of FRPs to produce a well-defined surface and has surface delamination associated with the characteristics of the material and the cutting parameters used. The surface quality and dimensional precision greatly affect the parts during their useful life, especially in cases where the components come in contact with other elements or materials. Optimization of machining parameters is an important step in machining. Taguchi’s L27 orthogonal array, milling experiments were conducted for GFRP composite plates using solid carbide end mills with different helix angles. The machining parameters such as, spindle speed, feed rate, helix angle and fiber orientation angle are optimized by multi-response considerations namely surface roughness, delamination factor and machining force. Feed forward backpropagation fuzzy logic and is trained and tested with pairs of input/output data. A very good performance of the fuzzy logic, in terms of good agreement with the experimental data has been achieved.

Author:

B. Anjaneyulu

Biographie:

Mr.B. ANJANEYULU has keen interest on technological developments on Manufacturing, Machining and optimization of the Polymer,metal and ceramic composite materials.  Mr. D. Harsha Vardhan has Research Interest on various fields of Materials and Mechanical Engineering, including Material characterization, optimization, FEA and CFD  

Author:

D. Harsha Vardhan

Biographie:

Number of Pages:

100

Book language:

English

Published On:

2020-07-17

ISBN:

978-620-2-68041-7

Publishing House:

LAP LAMBERT Academic Publishing

Keywords:

GFRP Composites, Machining, Modeling, Taguchi, Design of Experiments, Fuzzy logic, Fuzzy Inference System (FIS), ANOVA

Product category:

TECHNOLOGY / Engineering / General