# Applications of Digital Twin across Industries: A Review
## 9 Mining  
The mining sector, which is dedicated to locating and extracting metal and mineral reserves from the earth's surface, is considered one of the oldest established industries [137]. Just as for the oil and gas industry, a DT is a perfect tool for process/operation optimization on mining sites. Ernst and Young has identified a DT as one of the key enabling technologies in the mining industry as it is going through digitalization [138]. In their report, they presented four areas where DTs contribute to mining: (i) Mining Operations: predictive maintenance improves asset reliability and cuts down unplanned downtime, (ii) Processing: optimizing plant set points improve the efficiency of processes and the quality of the product, and reduces bottleneck, (iii) Transport: predicting and optimizing the transport network improves transportation reliability, and (iv) End-to-End: simulating and analyzing different scenarios across the value chain determines optimal plans and schedules. Moreover, DTs help miners in testing new processes or machinery before using the real one on the site and also trains new miners [139], especially for emergency situations, by educating them about the correct procedure and training them remotely in a risk-free and stress-free environment [140].  
PETRA DataScience [141], a provider of digital mine-to-mill software for value chain optimization, created the world's first DT for the optimization of the mine value chain. Their machine learning DT uses two years of historical data to simulate'mine planning, blasting, metallurgy, and process control options.' The Ban Houayxai Gold-Silver Mine in Laos used the DT, which, using the data on the types of rock, optimized the crushing efficiency during drilling and blasting, thus increasing the recovery rate of the metal from the mine [142].  
Anglo American plc [143], a multinational mining company, is using the DT in their mining sites in Chile and Brazil to reduce the fuel consumption of their trucks, thus optimizing the mining fleet. By tracking the performance of the haulage fleet, they can analyze the data which is used for improving equipment efficiency, condition monitoring, and predictive maintenance. They are also planning to implement DT for their pipelines, smelters, and refineries to make the process more effective and efficient. Rio Tinto [144], the world's second-largest metals and mining corporation, also uses DT in the Gudai-Darri (Koodaideri) mine. Using a DT, they are safely testing new ways to improve their productivity without damaging any parts or halting any process within the plant.  
DT technology has the potential of adding new value to the mining industry, from increasing efficiency to providing a safer environment, which explains why mining corporations are investing in DT technology. The International Data Corporation (IDC), a global provider of market intelligence and advisory services, has predicted that 70% of the mining companies will be investing in DT technology in the next two years [145]. In addition, DT has caught national interest for the'revitalization of domestic resource development' [146].