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Optimization of Thermo-Mechanical Controlled Processing (TMCP) Using Swarm Intelligence

Shaheera Rashwan, Dina Abdelhafiz, Eman Hassan El-Shenawy, Bayumy A.B. Youssef

Abstract


In low carbon steel manufacturing, the thermo-mechanical controlled processing (TMCP) has been developed as a grain refinement method that performs a noticeable upgrading in productivity and service performance. Optimizing TMCP by choosing the best strain rate through experiments in labs requires so much effort, time, and cost. In this paper, we developed a new technique based on solving the Zener-Holloman parameter equation via swarm intelligence to get the best strain rate that enhances grain refinement. We applied our new technique in one pass, two passes and four passes TMCP strategies for different values of temperature. We used the mean absolute error (MAE) as a quality eliability of the findings and demonstrate how effective the new method is.


Keywords


Thermo-mechanical controlled processing (TMCP), particle swarm optimization (PSO), applied computing chemistry, low carbon steel manufacturing, Zener-Holloman (Z-H)

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References


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