Predicting Particle Fineness in a Cement Mill
Researcher: Rowan Lange, University of the Witwatersrand, Johannesburg
Supervisors: Prof. Anton van Wyk, Dr. Terence van Zyl
Cement production is a multi-billion dollar industry, of which one of the main subprocesses, cement milling, is complex and non-linear. There is a need to model the fineness of particles exiting the milling circuit in order to better control the cement plant. This paper explores the relationship between the particle size of cement produced and various sensor readings from the cement mill circuit. The aim of this paper is 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 large cement plant. On a holdout test set a multi layered perceptron achieved a 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 success from non-linear data-driven models and highlight the unique difficulties in modelling the cement mill, presenting recommendations for future research.