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Development of a kiln petcoke mill predictive model based on a multi-regression XGBoost algorithm

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Abstract

This paper presents an investigation into the optimization of petroleum coke mill or petcoke mill processes, to improve efficiency and reduce waste in the heavy industry within the cement plant where our study is conducted. Our mission was to create a robust algorithm that could properly anticipate the mill’s performance and improve its operations. To accomplish this, we started by performing a comprehensive data analysis. Next, we built numerous regression models, and then assessed the effectiveness of each model using four crucial metrics. The suggested model is a multi-regression XGBoost (eXtreme gradient boosting) model, performing with a 90% score. Finally, the model will then be used to build an algorithm that can optimize the input values to accomplish the intended results.

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Acknowledgements

The authors would like to thank all the stakeholders of this project and particularly the engineers and technicians of the cement plant where our research was conducted.

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Authors and Affiliations

  1. Laboratory of Innovation and Systems Engineering; Mechanical and Structural Engineering Department; ENSAM, Moulay Ismail University, Meknes, Morocco

    Mohammed Toum Benchekroun, Smail Zaki & Mohamed Aboussaleh

  2. Artificial Intelligence & Data Science Department; ENSAM, Moulay Ismail University, Meknes, Morocco

    Hajar Belrhiti & Fatoumata Diassana

Authors
  1. Mohammed Toum Benchekroun
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  2. Smail Zaki
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  3. Mohamed Aboussaleh
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  4. Hajar Belrhiti
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  5. Fatoumata Diassana
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Contributions

All authors contributed to the study’s conception and design. Material preparation, data collection, and analysis were performed by M.T. Benchekroun, S. Zaki, M. Aboussaleh, H. Belrhiti, and F. Diassana. The first draft of the manuscript was written by M.T. Benchekroun, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Smail Zaki.

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Benchekroun, M.T., Zaki, S., Aboussaleh, M. et al. Development of a kiln petcoke mill predictive model based on a multi-regression XGBoost algorithm. Int J Adv Manuf Technol 130, 3373–3386 (2024). https://doi.org/10.1007/s00170-023-12689-z

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  • DOI: https://doi.org/10.1007/s00170-023-12689-z

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