Abstract
The present study highlights a quantum behaved particle swarm optimization approach combined with maximum deviation theory to determine the optimal process parameters in wire electrical discharge machining process during taper cutting operation. Experiments have been conducted using six process parameters such as part thickness, taper angle, pulse duration, discharge current, wire speed and wire tension each at three levels for obtaining the responses like angular error, surface roughness, and cutting speed. Taguchi’s L27 orthogonal array is used to gather information regarding the process with less number of experimental runs. Traditional Taguchi approach is insufficient to solve a multi response optimization problem. In order to overcome this limitation, maximum deviation method has been implemented, to convert multiple responses into equivalent single response called composite score. A process model has been developed by using non-linear regression analysis. Finally, optimal parameter setting is obtained by quantum behaved particle swarm optimization technique.
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Nayak, B.B., Mahapatra, S.S. (2015). A Quantum Behaved Particle Swarm Approach for Multi-response Optimization of WEDM Process. In: Panigrahi, B., Suganthan, P., Das, S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2014. Lecture Notes in Computer Science(), vol 8947. Springer, Cham. https://doi.org/10.1007/978-3-319-20294-5_6
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