Benefits and Possibilities of Artificial Intelligence and Robotics in the Mining Industry

Benefits and Possibilities of Artificial Intelligence and Robotics in the Mining Industry

The mining industry has experienced significant advancements in recent months thanks to the implementation of disruptive technologies. Among them, artificial intelligence (AI) and robotics have demonstrated enormous potential to improve operational efficiency, worker safety, and sustainability in mining.

In this article, we will explore some of the key benefits of AI and robotics in the current mining context, as well as some of the innovative applications that are transforming the industry worldwide.

Current Mining Context

The mining industry is one of the most important and dynamic industries in the world, as it provides essential raw materials for the economic and social development of many countries. However, it also faces significant challenges and opportunities in a changing global context, characterized by increasing demand for resources, competition for access to them, environmental and social pressure, technological innovation, and geopolitics.

Some of the challenges that the mining industry must face are:

• Reducing operating and capital costs by optimizing process efficiency and productivity, as well as managing financial and regulatory risks.
• Improving occupational and environmental safety by minimizing the negative impacts of mining activities on people and the environment, and complying with international quality and sustainability standards.
• Innovating and collaborating to develop technological solutions that enable the exploration of new deposits, increase resource recovery, reduce energy and water consumption, and improve waste treatment and recycling.
• Strengthening relationships with communities and stakeholders by generating shared value and social responsibility that contribute to local and regional development, while respecting human rights and local cultures.
• Educating and training the human resources required by the future mining industry, with technical, digital, environmental, and social competencies capable of adapting to sectoral changes and challenges.

Some of the opportunities that the mining industry can seize are:

• Increasing demand for minerals that are key to the energy transition and decarbonization of the global economy, such as copper, lithium, nickel, cobalt, and graphite, among others.
• Diversifying mineral supply sources by exploring new regions with geological potential, such as Latin America, Africa, or Central Asia, or harnessing existing resources in remote or deep areas.
• Implementing clean technologies and renewable energies that reduce the environmental footprint of mining activities, such as solar, wind, or hydroelectric energy, or the use of biofuels or green hydrogen.
• Cooperating regionally and internationally to exchange good practices, knowledge, and experiences in sustainable mining, as well as promoting a harmonized and transparent regulatory framework that provides legal certainty for investors.
• Promoting a circular economy in the mining industry by applying principles of ecological design, waste prevention and minimization, material reuse and recycling, and extending the lifespan of products.

Artificial Intelligence (AI) in Mining

Artificial intelligence (AI) is a branch of computer science that deals with creating systems capable of performing tasks that normally require human intelligence, such as learning, reasoning, perception, communication, and decision-making.

AI is based on algorithms that process large amounts of data to extract patterns, knowledge, and predictions.

AI offers multiple benefits for mining, including:

• Process optimization and decision-making: AI enables the analysis and optimization of mining processes at all stages, from exploration to closure, including planning, design, drilling, loading, transportation, processing, and maintenance. AI also facilitates data-driven decision-making, improving the efficiency and profitability of operations.
• Prediction and prevention of equipment failures: AI allows for monitoring the state and performance of mining equipment, such as drills, shovels, trucks, crushers, and mills, through sensors and telemetry systems. AI also enables anomaly detection, problem diagnosis, and prediction of potential failures, reducing downtime, repair costs, and accident risks.
• Advanced data analysis to improve efficiency and productivity: AI enables the processing and analysis of vast amounts of data collected from various sources in the mining industry. By utilizing machine learning algorithms, AI can identify patterns, trends, and correlations within the data to optimize processes, reduce waste, and increase productivity. This includes improving ore grade control, optimizing blasting parameters, and streamlining logistics and supply chain management.
• Safety and risk management: AI can play a crucial role in enhancing safety and risk management in mining operations. By integrating AI-powered monitoring systems, it becomes possible to detect and respond to safety hazards in real-time. For instance, AI algorithms can analyze sensor data to identify potential safety risks and issue alerts or automatically initiate safety protocols. This helps in preventing accidents, ensuring worker safety, and improving emergency response.
• Environmental monitoring and sustainability: AI can contribute to sustainable mining practices by enabling effective environmental monitoring and management. Through the analysis of environmental data, AI algorithms can detect and predict potential environmental impacts, allowing mining companies to proactively mitigate risks. Additionally, AI can assist in optimizing resource usage, energy efficiency, and waste management, thereby reducing the industry's ecological footprint.

Robotics in Mining

Robotics is the science and technology that deals with designing, building, and programming machines capable of autonomously or semi-autonomously performing tasks through the use of sensors, actuators, and control systems.

Robotics is applied in various fields and sectors, including mining.

Robotics offers several advantages for mining, such as:

• Performing dangerous and repetitive tasks: Robots can carry out tasks that involve high risks for human workers, such as inspecting inaccessible or dangerous areas, maintaining equipment in extreme conditions, handling explosive or toxic materials, among others. Robots can also perform tasks that are monotonous or require great precision, such as sampling or mineral analysis.
• Exploration and mapping of inaccessible areas for humans: Robots can explore and map areas that are difficult or impossible for humans to access. Robots can use different types of sensors, such as cameras, radars, lasers, or sonars, to obtain detailed information about the terrain and mineral resources.
• Automation of mining operations, such as drilling and transportation: Robots can automate mining operations that require extensive coordination and synchronization, such as drilling and material transportation. Robots can communicate with each other and with a control center to optimize resource usage and prevent collisions or accidents. Robots can also adapt to changing environmental conditions and respond to unforeseen situations.
• Increased precision and efficiency in mineral extraction: Robots can extract minerals with greater precision and efficiency than conventional methods, reducing waste and environmental impact. Robots can use advanced techniques for cutting, separation, and classification of minerals, as well as intelligent quality control and traceability systems. Robots can also enhance performance and recovery of mineral resources.

Applications of AI and robotics in the mining industry

AI and robotics are being used in various areas of mining with the aim of improving efficiency, safety, and sustainability of mining operations.

Some specific examples of these applications are:

• Drones and autonomous vehicles for inspection and monitoring: Drones and autonomous vehicles are aerial or ground devices that can fly or move autonomously or be remotely controlled. Equipped with cameras, sensors, and communication systems, these devices are used to inspect and monitor different aspects of mining operations. They can assess the condition of infrastructure, track progress in construction, ensure compliance with environmental and safety regulations, and detect anomalies or risks. Drones and autonomous vehicles provide real-time information, reduce operational costs, and minimize human exposure to dangerous or inaccessible environments.
• Use of machine learning algorithms to optimize mine planning: Machine learning algorithms are computer programs that can learn from data and improve their performance without explicit programming. These algorithms are used to optimize mine planning, which involves defining objectives, strategies, and actions for developing a mining operation. Machine learning algorithms analyze large amounts of historical and current data, such as geological characteristics, market prices, operational costs, available resources, and technical, legal, and environmental constraints. Based on this analysis, the algorithms can generate optimal or alternative scenarios to maximize the economic and social value of the mining operation.

• Use of algorithms to automate and improve the precision of post-blasting P80: Algorithms are logical sequences of instructions that solve a specific problem. These algorithms are used to automate and improve the precision of post-blasting P80, which refers to the size of 80% of the fragmented material after a blast. P80 is a key indicator for assessing the quality and efficiency of a blast, as it influences the performance and energy consumption of subsequent processes such as loading, transportation, and crushing. Algorithms enable the automatic and precise measurement of post-blasting P80 using digital cameras or drones that capture images of the fragmented material and process them using techniques of computer vision and artificial intelligence.
• AI-based gas detection and ventilation control systems: AI-based gas detection and ventilation control systems are intelligent systems that can detect the presence and concentration of hazardous gases in underground mines, such as methane, carbon monoxide, or sulfur dioxide. These systems rely on distributed sensors throughout the mine that send data to a control center, which analyzes the data using AI algorithms. These algorithms can generate early alerts in case of detecting critical or abnormal levels of gases and activate or regulate ventilation systems to maintain suitable air quality for workers.

• Real-time and predictive AI-based anti-fatigue systems: Real-time and predictive AI-based anti-fatigue systems are intelligent systems that can detect and prevent fatigue or drowsiness in drivers or mining operators. These systems rely on cameras or sensors installed in vehicles or mining equipment that capture images or physiological signals of the driver or operator, such as blinking, eye movement, heart rate, or blood pressure. These images or signals are processed using AI algorithms that can identify signs or patterns indicative of fatigue or drowsiness. The algorithms can generate auditory or visual alerts in case of detecting high or moderate levels of fatigue or drowsiness and suggest corrective or preventive actions, such as taking a break or changing activities.
• Augmented reality technology to enhance worker training and safety: Augmented reality technology overlays virtual elements onto the real environment using devices such as glasses, helmets, or smartphones. This technology is used to improve worker training and safety in mining by providing relevant real-time information about the environment or the task at hand. For example, augmented reality can display step-by-step instructions for performing a specific task, indicate hazardous zones or critical points in a mining facility, provide data on the status or operation of mining equipment, among other applications.

AI and robotics have the potential to transform the mining industry into a safer, more efficient, and sustainable sector. However, the adoption of these technologies also presents challenges, such as worker training, required investment, and legal and ethical implications. Despite these challenges, it is clear that mining is moving towards a digital era, and AI and robotics are vital tools on this journey.

The intelligence artificial and robotics offer many other benefits and possibilities in the mining industry. Which do you consider will have the most impact?

In the following articles, we will address how to tackle these challenges, being more specific about the opportunities with AI and robotics in the mining industry. Stay tuned!