Version 1
: Received: 11 October 2024 / Approved: 12 October 2024 / Online: 12 October 2024 (10:28:39 CEST)
How to cite:
Moon, S.; YOO, J. Operating key factor Analysis of a Rotary Kiln Using Predictive Model and Shapley Additive Explanations. Preprints2024, 2024100970. https://doi.org/10.20944/preprints202410.0970.v1
Moon, S.; YOO, J. Operating key factor Analysis of a Rotary Kiln Using Predictive Model and Shapley Additive Explanations. Preprints 2024, 2024100970. https://doi.org/10.20944/preprints202410.0970.v1
Moon, S.; YOO, J. Operating key factor Analysis of a Rotary Kiln Using Predictive Model and Shapley Additive Explanations. Preprints2024, 2024100970. https://doi.org/10.20944/preprints202410.0970.v1
APA Style
Moon, S., & YOO, J. (2024). Operating key factor Analysis of a Rotary Kiln Using Predictive Model and Shapley Additive Explanations. Preprints. https://doi.org/10.20944/preprints202410.0970.v1
Chicago/Turabian Style
Moon, S. and JEHYEUNG YOO. 2024 "Operating key factor Analysis of a Rotary Kiln Using Predictive Model and Shapley Additive Explanations" Preprints. https://doi.org/10.20944/preprints202410.0970.v1
Abstract
The global smelting business of nickel using rotary kilns and electric furnaces is expanding due to the growth of the secondary battery market. Efficient operation of electric furnaces requires consistent calcine temperature in rotary kilns, which involves shearing processes. Direct measurement of calcine temperature in rotary kilns presents challenges due to inaccuracies and operational limitations, and while AI predictions are feasible, reliance on them without understanding influencing factors is risky. To address this challenge, various algorithms including XGBoost, LightGBM, CatBoost, and GRU were employed for calcine temperature prediction, with CatBoost achieving the best performance, followed by XGBoost, LightGBM, and GRU in terms of MAPE. The influential factors on calcine temperature were identified using SHAP from XAI in the context of the CatBoost model. By incorporating seven out of twenty operational factors, the calcine temperature increased from 840℃ in 2023 to 907℃ by April 2024, concurrently reducing the power ratio of the electric furnace by 7.8%.
Keywords
Pyrometallurgy; Rotary kiln; CatBoost; XAI; SHAP
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
