Predicting particle fineness in a cement mill

Cement production is a multi-billion dollar industry, of which one of the main sub-processes, cement milling, is complex and non-linear. There is a need to model the fineness of particles exiting the milling circuit to better control the cement plant. This paper explores the relationship between the particle size of cement produced and the operation of the cement mill circuit. This paper aims to provide a model for predicting the fineness of particles exiting the milling circuit using data on the current and past states of the plant. A comprehensive literature review of the problem, as well as a discussion of potential modelling solutions, is provided. Blaine (particle fineness)is modelled using many different linear and non-linear models on 5 months of data from a Chinese cement plant. On a holdout test set a multi-layered perceptron achieved an MAE of 8.799 and a linear regression achieved a R² of 0.481. discussion of the significance of various features for predicting Blaine is also presented. The results show some limited success from non-linear data-driven models and highlight some of the unique difficulties in modelling the cement mill and present recommendations for future research.