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                Development of an Advanced Multi-Layer Digital Twin Conceptual Framework for Underground Mining            
            
            
            
            
            
                
                    
                            1
                        Department of Civil Engineering, Universidad de Castilla-La Mancha, Av. Camilo Jose Cela s/n, 13071 Ciudad Real, Spain
         
                    
                            2
                        School of Civil Engineering, Pontificia Universidad Católica de Valparaíso, Av. Brasil 2147, Valparaíso 2340000, Chile
         
                    
                            3
                        Department of Civil and Environmental Engineering, Universitat Politècnica de Catalunya, BarcelonaTech, C/Jordi Girona 1-3, 08034 Barcelona, Spain
         
    
    
            
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                Sensors 2025, 25(21), 6650; https://doi.org/10.3390/s25216650 (registering DOI)
            
            
                    
    Submission received: 2 October 2025
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    Revised: 21 October 2025
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    Accepted: 28 October 2025
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    Published: 30 October 2025
            
                
    
            
            
                        
            
            
            
        
                        
        
                        
        
                        
        
        
                        
        
                        
                                                                            
                                                                            
            
                            Abstract
            
            
                                                            Digital mining has been evolving in recent years under the Industry 4.0 paradigm. In this sense, technological tools such as sensors aid the management and operation of mining projects, reducing the risk of accidents, increasing productivity, and promoting business sustainability. DT is a technological tool that enables the integration of various Industry 4.0 technologies to create a virtual model of a real, physical entity, allowing for the study and analysis of the model’s behavior through real-time data collection. A digital twin of an underground mine is a real-time, virtual replica of an actual mine. It is like an extremely detailed “simulator” that uses data from sensors, machines, and personnel to accurately reflect what is happening in the mine at that very moment. Some of the functionalities of an underground mining DT include (i) accurate geometry of the real physical asset, (ii) real-time monitoring capability, (iii) anomaly prediction capability, (iv) scenario simulation, (v) lifecycle management to reduce costs, and (vi) a support system for smart and proactive decision-making. A digital twin of an underground mine offers transformative benefits, such as real-time operational optimization, improved safety through risk simulation, strategic planning with predictive scenarios, and cost reduction through predictive maintenance. However, its implementation faces significant challenges, including the high technical complexity of integrating diverse data, the high initial cost, organizational resistance to change, a shortage of skilled personnel, and the lack of a comprehensive, multi-layered conceptual framework for an underground mine digital twin. To overcome these barriers and gaps, this paper proposes a strategy that includes defining an advanced, multi-layered conceptual framework for the digital twin. Simultaneously, it advocates for fostering a culture of change through continuous training, establishing partnerships with specialized experts, and investing in robust sensor and connectivity infrastructure to ensure reliable, real-time data flow that feeds the digital twin. Finally, validation of the advanced multi-layered conceptual framework for digital twins of underground mines is carried out through a questionnaire administered to a panel of experts.
                    
                            
            
                            
            
                        
                        
                        
                    
                        
            
            
    
        
     
            
                Share and Cite
                
                
                    
MDPI and ACS Style
                    Cacciuttolo, C.;                     Atencio, E.;                     Komarizadehasl, S.;                     Lozano-Galant, J.A.    
        Development of an Advanced Multi-Layer Digital Twin Conceptual Framework for Underground Mining. Sensors 2025, 25, 6650.
    https://doi.org/10.3390/s25216650
    AMA Style
    
                                Cacciuttolo C,                                 Atencio E,                                 Komarizadehasl S,                                 Lozano-Galant JA.        
                Development of an Advanced Multi-Layer Digital Twin Conceptual Framework for Underground Mining. Sensors. 2025; 25(21):6650.
        https://doi.org/10.3390/s25216650
    
    Chicago/Turabian Style
    
                                Cacciuttolo, Carlos,                                 Edison Atencio,                                 Seyedmilad Komarizadehasl,                                 and Jose Antonio Lozano-Galant.        
                2025. "Development of an Advanced Multi-Layer Digital Twin Conceptual Framework for Underground Mining" Sensors 25, no. 21: 6650.
        https://doi.org/10.3390/s25216650
    
    APA Style
    
                                Cacciuttolo, C.,                                 Atencio, E.,                                 Komarizadehasl, S.,                                 & Lozano-Galant, J. A.        
        
        (2025). Development of an Advanced Multi-Layer Digital Twin Conceptual Framework for Underground Mining. Sensors, 25(21), 6650.
        https://doi.org/10.3390/s25216650
    
 
                 
                                    
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