Optimization of Specific Energy Consumption in Turning of GFRP Composites using Particle Swarm Optimization
Syed Altaf Hussain1, Palani Kumar.K2, Md.Alamgir3
1Syed Altaf Hussian*, Department of Mechanical Engineering, Rajeev Gandhi Memorial College of Engg. & Tech, Nandyal, (A.P), India.
2Palani Kumar. K. Sri Sairam Institute of Technology, Chennai, India.
3Md.Alamgir, Department of Mechanical Engineering, Rajeev Gandhi Memorial Colege of Engg. & Tech., Nandyal (A.P), India.
Manuscript received on May 03, 2021. | Revised Manuscript received on May 06, 2021. | Manuscript published on May 30, 2021. | PP: 11-17 | Volume-10 Issue-7, May 2021 | Retrieval Number: 100.1/ijitee.G88900510721| DOI: 10.35940/ijitee.G8890.0510721
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper, an attempt is made to optimize the control parameters for the minimization of specific energy consumption in turning GFRP composites using particle swarm optimization (PSO).Optimization of specific energy consumption in machining is helpful to evaluate the process energy characteristics and also facilitates choosing the best control parameters for energy saving. The control parameters considered are cutting speed, feed, depth of cut and fiber orientation angle. Experiments are planned and executed according to Taguchi’s L25 orthogonal array in the design of experiments on an all geared lathe with PCD cutting tool insert. A quadratic predictive model was developed for specific energy consumption using RSM and the optimal combinations of control parameters were determined using PSO. The Predicted results from PSO show that there is an improvement in MRR by 46.44% and a reduction in SEC by 33.69%. From the confirmative experimental results, it is observed that PSO algorithm has a powerful global search ability to solve the optimization problem.
Keywords: GFRP Composites, Taguchi Method, Turning, Specific Energy Consumption, PCD Tool Insert, Particle Swarm Optimization (PSO).