These technologies are critical to the present and the future of mining
Automation and Machine Learning are essential for the advancement of the mining industry. These technologies are being integrated into various aspects of the mining process, including exploration, drill targeting, equipment maintenance, and safety, among many others. However, there is a shortage of skilled personnel in these areas, leading to intense competition for talent in the field.
The University of Arizona School of Mining and Mineral Resources offers a unique program that integrates advanced technology with mining processes, preparing the next generation of mining and mineral resource professionals to take on top priorities for the mining industry, including safety and sustainability. We advance mining education by integrating different disciplines into effective problem solving, new technology application, research, and development, thanks to innovation-minded faculty, strong industry partnerships and our very own proving ground in the university-owned San Xavier Mining Laboratory.
Industry Partners
Tucson has a rich mining ecosystem, with plenty of mining industry providers and representatives having a presence nearby. This provides our faculty and students with easy access to some of the most innovative companies in the world. Faculty routinely connect with company leaders to share ideas and gain insight on the industry’s most pressing technological challenges, and these leaders provide lectures to our students on timely real-world mining topics. Plus, our students are often top picks for coveted internships in which they get to put their mining and technological knowledge to use in meaningful ways. We invite mining partners to reach out to the school of mining to learn more about collaboration opportunities with the School.
Research and Innovation
As mining landscapes evolve, so must our approaches to mineral resource extraction. Our renowned research faculty is innovating how automation and machine learning can be used to make mining more efficient so human workers can focus on more-interesting, complex problems. We are also seeking to develop fully autonomous mining systems that can adapt to treacherous environments, including flooded underground mines, seafloor mines and, eventually, space mining. Current research projects involving automation and machine learning include:
- Dust characterization and wind modeling
- Safety gear detection
- 4-D autonomous environmental monitoring systems
- Financial modeling
- Automated mine hazard detection