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- W2956920668 abstract "In steel recycling process, a lot of scrap is generated and it is used widely for producing steel. Nearly 40% of the world steel is produced by scrap steel recycling process. The main issue in recycling process is producing a quality steel out of scrap with minimum energy consumption. The parameters which influence the recycling process are furnace temperature, sponge steel addition percentage, scrap steel composition, TDS number of water used, and quenching temperature of steel. In this paper, an optimization model for maximizing tensile strength and hardness number value as objective function and energy consumption rate as a constraint is obtained by using response surface methodology. The detailed optimization model is solved by using state-of-the-art optimization technique called particle swarm optimization algorithm. Optimization values obtained are evaluated using experimentally and compared with other optimization techniques like Grey Taguchi. The optimum results obtained by particle swarm optimization (PSO) method outperform other techniques." @default.
- W2956920668 created "2019-07-23" @default.
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- W2956920668 date "2019-07-10" @default.
- W2956920668 modified "2023-09-26" @default.
- W2956920668 title "Optimization of Parameters for Steel Recycling Process by Using Particle Swarm Optimization Algorithm" @default.
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- W2956920668 doi "https://doi.org/10.1007/978-981-13-8196-6_9" @default.
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