For decades, new technologies have changed the way mining is practiced. More recently, technology has significantly contributed to the speed and quality of mining operations worldwide.
Some emerging technologies, such as drones and robotics, are increasingly replacing labor. Others, such as artificial intelligence, the Internet of Things, machine learning, and smart sensors, are increasing production without significantly reducing employment. In various contexts, these technologies will have varying effects. For instance, countries with greater economic diversity will be less adversely affected by changes in the labor market, and the adoption of particular technologies will depend on the situation.
New positions are being created for those skilled in GIS mapping, data processing, and software creation. Compared to the occupations they often supplant, including blasting, hauling, and drilling, these tend to pay better. In some circumstances, technological advances boost sustainability to the point that the considerably expanded scope of operation will boost the labor market even while employment per ton of ore mined is declining.
In addition to lowering average site expenses, digitization and analytics can improve safety, extend the lifespan of a mine, and boost the reserve base. The reserve base is the mine’s existing resources that meet the current mining practice criteria, such as ore quality. According to McKinsey, by 2035, self-driving mining enabled by data analysis and digital innovations like artificial intelligence will have saved mineral raw material companies from $290 billion to $390 billion yearly. In their daily administration and operations, most mining businesses are moving away from empirical models toward AI.
Additionally, they are converting from inflexible workforce scheduling to more dynamic models, with a multifaceted team concentrating on the most important areas and switching from plug-and-play technologies to many value-driven, bespoke techniques adapted to specific requirements.
Condition-based, reactive, prescriptive, preventive, and predictive maintenance are the five basic maintenance techniques that mining engineers adopt to ensure their machinery is properly functioning and maintained. Predictive maintenance takes the condition-based approach a step further by utilizing design-based detection of anomalies, including the online collection of sensor data, and applying data analytics to forecast machine dependability. Mining businesses are starting to utilize condition-based maintenance to cut costs, improve utilization, and prolong asset life by collecting information from IoT sensors, enabling them to assess every asset's health in real-time and forecast failure timing.
Some mining operations are now using autonomous trucks to improve safety while decreasing fuel consumption by 10-15 percent, as well as reducing risk at work sites and in adjacent areas. GlobalData research showed 1,068 automated haul trucks were operating worldwide in 2022. Currently, 30 to 50 percent of all primary emissions of greenhouse gases at mine sites are produced by mining vehicles.
The new technologies may have favorable social and environmental effects that will balance out the detrimental effects on labor. For instance, the data-connected mines of the future will provide residents living close by with real-time information on procedures, water quality, and tailings dam indicators. It may also provide tax authorities with improved data on output levels. Altogether, these changes are expected to result in more women gaining employment in distant operations centers, improved safety and health for employees, a decrease in emissions of greenhouse gases, and collaborative infrastructure like fast broadband and renewable power with an opportunity to stimulate economic growth.