Por: Andrea Rivera, Sandra Jara y Geraldine Quispe, Greatt de Innovación, Wim Perú.

Abstrac

The global mining industry is undergoing a period of rapid transformation driven by increasing demands for productivity, sustainability, safety, and energy efficiency. In this context, digital twins have emerged as one of the most promising technologies for optimizing complex operations and improving real-time decision-making. 

A digital twin integrates operational data, mathematical models, advanced simulation, and artificial intelligence to create a virtual representation of equipment, circuits, or industrial processes. 

This article reviews the fundamental principles, operating modes, and reference architecture of digital twins applied to mineral processing and examines two case studies from the Peruvian mining industry. 

The results demonstrate tangible benefits in operational stability, reduced process variability, faster ramp-up, and enhanced support for predictive maintenance, particularly in grinding circuits. The study also identifies critical challenges related to interoperability between OT and IT systems, data quality and governance, cybersecurity, and organizational change management. 

Finally, technical and organizational guidelines are proposed for the effective adoption of digital twins in the context of the Peruvian mining industry, highlighting their role as enablers of more efficient, safer operations oriented toward autonomy and continuous optimization.