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Improvement of Surface Roughness by Particle Swarm Optimization in Hot Air Streaming Turning Process of Mild Steel

Md. Anayet U. Patwari, Mohammad Ahsan Habib, Md. Minhazul Islam, and Md. Firoz Mahmud
Department of Mechanical and Chemical Engineering, Islamic University of Technology, Dhaka, Bangladesh

Abstract— In machining operation, the quality of surface finish is an important concern for many finished work products. Thus, the choice of optimized cutting parameters like speed, feed and depth of cut is very important for controlling the required surface quality. The focus of present experimental study is to optimize the cutting parameters using the surface roughness as performance measure. The experimental result shows that the work piece surface roughness can be used effectively as a beacon to control the cutting performance. The modeling of the experimentally obtained data is being done using the regression analysis. Optimal cutting parameter for performance measure is obtained employing Particle Swarm Optimization (PSO) in order to get the minimum surface roughness and compared with the experimentally obtained data. The adequacy of the models of surface roughness has been established to achieve minimum surface roughness. 

Index Terms— hot air, surface roughness, turning operation, optimization, convergence, particle swarm optimization

Cite: Md. Anayet U. Patwari, Mohammad Ahsan Habib, Md. Minhazul Islam, and Md. Firoz Mahmud, "Improvement of Surface Roughness by Particle Swarm Optimization in Hot Air Streaming Turning Process of Mild Steel" International Journal of Mechanical Engineering and Robotics Research, Vol. 8, No. 4, pp. 588-593, July 2019. DOI: 10.18178/ijmerr.8.4.588-593