Abstract
In order to investigate the effect of parameters and system optimization, the processes must be modeled first. Cement rotary kiln systems are complex because of non-linear, time invariant and full of behavioral uncertainty where the mathematical modeling of the plant is impossible. Artificial neural network (ANN) is one of the best tools for improving the performance of such processes. In this study, the operational data from a cement factory are gathered and the relationships between variables analyzed via using ANN via MATLAB toolbox. ANN proposed 2.7 and 865 rpm for kiln and fan motor speed respectively and 4599.7 Ncm/h for total grate flowrate as optimum values. This research shows that using ANN for improving the performance of rotary kiln is effective and by optimization of operational parameters through ANN and applying them in the rotary kiln, higher production in the cement industry is accessible.
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Acknowledgements
This research was done by supporting of Arta Ardabil Cement Co. All the data used, were obtained from this factory's production line. We thank the Arta Ardabil Cement factory management for supporting us in duration of doing this project.
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This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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Aghdasinia, H., Hosseini, S.S. & Hamedi, J. Improvement of a cement rotary kiln performance using artificial neural network. J Ambient Intell Human Comput 12, 7765–7776 (2021). https://doi.org/10.1007/s12652-020-02501-1
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DOI: https://doi.org/10.1007/s12652-020-02501-1