Scientists Use a Smart Decision Tool to Pick the Best Mining Trucks and Shovels

Scientists have built a new decision-making tool to help mining companies choose the best trucks and shovels for their mines. The study focused on Gol-E-Gohar Mine No. 3, a large iron ore mine in Kerman Province, Iran. Researchers wanted to find which mix of equipment works best at different points in a mine's life. Instead of making one fixed choice, they used a smart method that changes as the mine's needs change over time.

Picking the wrong mining equipment can cost companies millions of dollars. Mines go through different stages, much like people go through different phases of life. At first, a mine needs machines that can move huge amounts of material quickly. Later, keeping costs low becomes more important, and near the end of a mine's life, protecting the environment matters most.

The team built a method called Dynamic Multi-Criteria Decision Making, or DMCDM. The word 'dynamic' means it moves and adjusts, just like the mine does. This tool looks at past decisions to help make better ones in the future. It also considers many different factors at once, instead of focusing on just one thing like cost or speed.

Inside this tool, the researchers used a technique called the Analytic Network Process, or ANP. Think of ANP like a web of connected ideas where each factor can affect the others. For example, buying bigger equipment might lower long-term costs but raises the upfront price. ANP helps map out all these connections so decision-makers can see the full picture before choosing.

The researchers divided the mine's life into three main phases. The first is 'pre-mining,' which covers planning before any digging starts. The second is the active 'mining' stage, when workers pull iron ore from the ground. The third is 'post-mining,' when ore runs out and the focus shifts to cleaning up and restoring the land.

The team looked at four different equipment combinations, called Scenarios A, B, C, and D. Each used a different mix of large shovels, loaders, and haul trucks. They measured each scenario using four key factors: capacity, capital cost, operational cost, and carbon dioxide emissions. This gave them a clear way to compare all four options side by side.

To weigh each factor, the team asked 25 mining experts for their opinions. These experts included university professors, graduate students, and professional engineers. About 40 percent had direct experience at Gol-E-Gohar Mine No. 3, making their input especially useful. Their survey answers were averaged together to create a final set of weights for the model.

The results showed clear patterns across each stage. In the early stage, production capacity made up about 40 percent of the decision weight. During the middle stage, operational costs rose to the top at around 41 percent. By the final stage, carbon dioxide emissions became the leading concern at nearly 40 percent.

Gol-E-Gohar Mine No. 3 is one of Iran's most important mining sites, located about 55 kilometers southwest of Sirjan. Despite its desert location, the mine is well connected by a major highway and a railway line just 8 kilometers away. A private rail link also connects it directly to Iran's national railway system. This strong infrastructure helps the mine ship iron ore quickly and at lower cost.

The researchers believe their method can be used at mines around the world. Mining companies everywhere face the same challenge: needs change over the years, but equipment bought today may still be running decades from now. By planning smartly at each stage, companies can save money, improve safety, and reduce environmental damage. This study shows that a flexible, step-by-step decision tool can help achieve all of those goals at once.