Abstract
Beside all the challenges regarding climate change, resources scarcity and quality degradation of deposits, the mining industry is becoming an environment that is constantly under pressure and restrictive. The increasing of raw materials prices, the unstable and high volatile commodity prices, the decreasing ore grades and the rising energy cost have shown a clinical impact on the mining sector. One way to mitigate the variability caused by these external forces is to take advantage of the latest advanced information technologies and set up an innovative strategy to optimise the processing cost. A key enabler for the optimisation of the mineral processing value chain and for the digital disruption of the mining sector is the Digital Twin. Digital Twin encompasses digital models of the production models enabling a virtual representation of a physical system and ensuring a continuous real time interaction, correction, control and optimisation. Consequently, the Digital Twin could afford an alleviation of the mineral processing variability in terms of mineralogy, final product’s grades, mechanical setting and processing configuration. This topic is a part of the Moroccan national project “Smart Connected Mine” that arose after the consortium of industrials and researchers for the digital transformation of the mining industry. In this paper, the background of the Digital Twin, its types and the major misconceptions about it are presented. The values, challenges of the implementation of such concept and its key enablers technologies are highlighted. Also an architectural framework for the Digital Twin implementation in a mineral processing plant is proposed and the modeling approaches are discussed.
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Acknowledgement
This work is supported by the Ministry of Higher Education, Scientific Research and Innovation, the Digital Development Agency (DDA) and the CNRST of Morocco through Al-Khawarizmi program. This publication is part of the work undertaken by the consortium of partners which is composed of MAScIR (Moroccan Foundation for Advanced Science, Innovation and Research), Reminex; the R &D and Engineering subsidiary of Managem group, UCA, ENSIAS and ENSMR. We would like to thank the Managem Group and its subsidiary CMG for allowing the conduction of this research on its operational site as an industrial partner of this project.
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Hasidi, O. et al. (2022). Digital Twins-Based Smart Monitoring and Optimisation of Mineral Processing Industry. In: Hamlich, M., Bellatreche, L., Siadat, A., Ventura, S. (eds) Smart Applications and Data Analysis. SADASC 2022. Communications in Computer and Information Science, vol 1677. Springer, Cham. https://doi.org/10.1007/978-3-031-20490-6_33
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