Process Prediction Using Machine Learning Techniques Applied to Cement Industry

Abstract

Abstract In the context of organizing the means of production, the heavy cement industry is following the new concept of Industry 4.0, which increases the efficiency of industrial processes and increases productivity through customization and flexibility, while reducing costs and energy consumption. To do this, it uses process prediction by operating the digital transformation through a 4.0 tool for monitoring and analyzing temperature and pressure in real time. This tool monitors temperature and pressure using sensors that transform the data into a computer platform for real-time analysis, and predicts failures according to a predictive model to remedy the problem of preheater cyclone blockages. This new technology reduces incidents and increases the life of equipment [1].