What Does ‘World Environment Day’ Mean for Mining?

World Environment Day holds significant implications for the mining industry. It serves as a reminder of the industry’s responsibility to minimize its environmental footprint and promote sustainable practices.

Mining operations often have substantial impacts on ecosystems, water resources, and air quality. Therefore, on World Environment Day, mining companies are encouraged to reflect on how they are applying concrete actions and processes toward sustainability initiatives and explore ways to reduce pollution, conserve resources, and mitigate environmental degradation, particularly through the utilization of innovative and digital technologies.

AI-driven solutions offer mining companies a range of tools and techniques to address the challenges of ensuring a sufficient and sustainable supply of critical resources like copper. By harnessing the power of AI, mining operations can become more efficient, productive, and environmentally responsible, contributing to the long-term viability of the industry.

However, how can they practically make use of this?

Where Do Digital Solutions Come In?

Mining companies can practically work towards sustainability initiatives and reduce their environmental impact by making their operations more efficient using digitalization strategies, such as:

Customer implementation

Data Analytics and Predictive Modeling: Leveraging data analytics and predictive modeling techniques such as objective-driven AI to analyze vast amounts of data from mining operations. This can help identify areas for improvement and give recommendations in energy efficiency, waste reduction, and resource optimization.

By predicting potential environmental impacts and operational inefficiencies, mining companies can take proactive measures to mitigate risks and improve sustainability.

Automation and Robotics: Implementing automation and robotics technologies to optimize mining processes reduce the environmental footprint and increase safety. Automated equipment can operate more efficiently, minimizing energy consumption and reducing emissions.

Remote Monitoring and Control Systems: Utilizing remote monitoring and control systems to enable real-time monitoring of mining operations from a centralized location. This allows for better management of environmental impacts, such as air and water quality monitoring, as well as minimizing energy usage and emissions. 


By leveraging digitalization in these areas, mining companies can enhance their sustainability practices and minimize their environmental impact while maximizing operational efficiency and safety.

Getting Started with Objective-driven AI

Artificial intelligence offers multiple methodologies for problem-solving, with ‘objective-driven AI’ emerging as a stronger approach for real-time process optimization applications in the Mining industry.

Unique to this approach is its adaptability; objectives can be adjusted in real-time without the need for exhaustive model retraining with new data.

In dynamic environments like mining operations, objective-driven AI can mitigate some of the pitfalls of other modern AI approaches and enhance efficiency and safety by offering a combination of first principles and data-driven, flexible decision-making that closely resembles human planning and evaluation.

Customer implementation

Within the realm of plant operations, the IntelliSense.io real-time Thickener Optimization Application exemplifies the capabilities of the objective-driven AI paradigm and it can help save more water.

At the core of the application is the world model which consists of a Bayesian deep neural network supported by virtual sensors based on first principle calculations. The thickener optimizer proposes actions in the form of future control settings, and it evaluates the predicted outcomes of those actions, considering multiple aspects and guard rails of the thickener operation.

Therefore, users can make more informed decisions based on their sustainability targets. Moreover, these optimized scenarios significantly enhance efficiency, resulting in improved water recovery (producing clear water in the overflow), reduced energy consumption (through optimized rake and lift use), and increased mineral recovery crucial for the energy transition.

Interested in learning how this can be applied to your operations?

Mine to Market: Value Chain Optimization

The Stockpile & Inventory Optimization Application is one of a suite of real-time decision-making applications that uses AI to optimize each process; from mine to market.

Our Material Handling model connects these applications to drive even greater efficiency.

Our process optimization apps can be deployed on a specific process bottleneck or expanded across the entire value chain. They are powered by our Industrial AI Decision Intelligence Platform, brains.app.

Stockpile and Inventory Optimization

Stockpile & Inventory Optimization

Grinding Optimization App

Grinding Optimization

Thickener Circuit Optimization

Thickener Optimization

Flotation Circuit

Flotation Optimization

Solvent Extraction Optimization App

Solvent Extraction (SX) Optimization

Leaching Optimization App

Leaching Optimization