Modeling operational cement rotary kiln variables with explainable artificial intelligence methods - a "conscious lab" development

• Published in: Particulate science and technology Vol. 41; no. 5; pp. 715 - 724
• Main Authors: Fatahi, Rasoul, Nasiri, Hamid, Homafar, Arman, Khosravi, Rasoul, Siavoshi, Hossein, Chehreh Chelgani, Saeed
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 04.07.2023; Taylor & Francis Ltd
• Subjects: Artificial intelligence; cement industry; Cement plants; Clinker; digitalization; Digitization; Energy consumption; Explainable artificial intelligence; Feed rate; Kilns; machine learning; Mineral Processing; Mineralteknik; Modelling; Rotary kiln

Digitalizing cement production plants to improve operation parameters' control might reduce energy consumption and increase process sustainabilities. Cement production plants are one of the extremest CO 2 emissions, and the rotary kiln is a cement plant's most energy-consuming and energy-w...