IJMTES – OPTIMIZING AND FORECASTING THE MACHINING VARIABLES OVER THE OUTPUT PARAMETERS IN TURNING OF GFRP COMPOSITES THROUGH HYBRID GA SEED GSA ALGORITHM

Journal Title : International Journal of Modern Trends in Engineering and Science

Paper Title : OPTIMIZING AND FORECASTING THE MACHINING VARIABLES OVER THE OUTPUT PARAMETERS IN TURNING OF GFRP COMPOSITES THROUGH HYBRID GA SEED GSA ALGORITHM

Author’s Name : D Ramalingam | Dr M Saravanan | R Rinu Kaarthikeyen
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Volume 04 Issue 03 2017

ISSN no:  2348-3121

Page no: 214-218

Abstract –The applications of Glass Fibre Reinforced plastic (GFRP) have been ever-increasing significantly in numerous domains. Simultaneously the industrialized progression and manufacture techniques must be urbanized to make sure elevated accuracy and high-quality surface of the components. In consequence of this manufacturing situation, it is essential to examine the machining process. The present approach reports the experiments in turning of GFRP material, to optimize and predict the performance of the input process parameters with reference to the output parameters with heuristic algorithms. The experiments were carried out at various set of cutting parameters. Fruit fly optimization algorithm, Gravitational Search Algorithm, Intelligent water drop Algorithm and Genetic Algorithm optimization methodology was used. Based on the most optimized values hybrid algorithm is employed to predict the suitable set of cutting parameters towards the expected outcome and compared with the performance of the individual algorithm. It is concluded that the cutting conditions is enormously significant to obtain the optimized outcomes.

KeywordsGFRP, Turning, MINITAB, Fruit Fly Optimization Algorithm, Gravitational Search Algorithm, Intelligent Water Drop Algorithm, Genetic Algorithm, MATLAB, Tool Wear, Material Removal Rate, Surface Roughness

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