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- W2146308083 abstract "Optimization is necessary for the control of any process to achieve better product quality, high productivity with low cost. The grinding of silicon carbide is not an easy task due to its low fracture toughness, making the material sensitive to cracking. The efficient grinding involves the optimal selection of operating parameters to maximize the material removal rate (MRR) while maintaining the required surface finish and limiting surface damage. In this work, optimization based on the available model has been carried out to obtain optimum parameters for silicon carbide grinding via particle swarm optimization (PSO) based on the objective of maximizing MRR with reference to surface finish and damage. Results obtained are superior in comparison with genetic algorithm (GA) approach." @default.
- W2146308083 created "2016-06-24" @default.
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- W2146308083 date "2006-10-11" @default.
- W2146308083 modified "2023-09-26" @default.
- W2146308083 title "Performance Analysis of Grinding Process via Particle Swarm Optimization" @default.
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- W2146308083 doi "https://doi.org/10.1109/iccima.2005.45" @default.
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