Tucson Standard

From mapping ore to predicting slope behavior and reclaiming land, the mining industry is rapidly evolving with technology. However, planning and operations have not always kept pace with these advancements.

With a $1.25 million grant from the National Institute for Occupational Safety and Health (NIOSH), researchers in the University of Arizona College of Engineering are working to better align technology and planning for improved safety and productivity in mining. The award will fund research for six graduate students over the next five years.

"With this award, we are able to train graduate students in important areas and generate cutting-edge research that not only adds to the body of knowledge but also contributes to the mining industry," said associate professor Angelina Anani, who leads the project alongside professor Moe Momayez and assistant professor Nathalie Risso.

The demand for minerals such as copper, lithium, and cobalt—essential for technologies like laptops and electric vehicles—is at an all-time high. The United States heavily relies on foreign countries for its supply, with estimates suggesting more than 80% of its minerals come from abroad. A renewed federal focus on American-made products challenges the mining industry to boost productivity while maintaining worker safety.

These NIOSH-funded projects aim to improve every aspect of a mine's lifecycle—from rock assessment to post-mine land use—potentially transforming how mines are planned and operated. Anani's team is exploring dynamic mine planning, which utilizes big data collected during production fed into artificial intelligence models to provide operators with timely information for better decision-making.

"We have not figured out the best way to extract information from that data and apply it to operations in a sustainable way," Anani stated. "Our idea is to take that data and update each stage of the mine planning process by using technologies such as machine learning."

Professor Moe Momayez focuses on advanced geotechnical methods for evaluating subsurface conditions and mapping ore deposits. Mines currently rely on exploratory boreholes, but deposits can stretch for miles. "We're focusing on using geophysical techniques to create a continuous map of geological properties and ore grade before mining," he explained.

Assistant professor Nathalie Risso directs efforts toward aligning automation with safety regulations. "There are a lot of standard operating procedures associated with how mining equipment is supposed to work," she noted. "But when you have autonomy, those are not going to apply, so with this research we seek to create new methods to make mining safer and more productive."

The researchers study autonomous mining vehicles used internationally and plan recommendations for updated U.S. regulations. Doctoral student Tinotenda Blessing Chimbwanda emphasizes safety: "Autonomous vehicles bring new risks in terms of how they interact with other equipment... The whole idea about mining for me is to make sure that everyone goes home safe and uninjured."

Chimbwanda is one of six graduate students supported by the CDC award; funding remains available for five additional students under professors Anani, Risso or Momayez.