Surging Copper Demand Sparks Exploration of AI Solutions to Boost Production

Copper is essential for the energy transition as the world becomes more electrified. BHP’s recent bid for Anglo American has stirred the market, emphasizing the surging copper demand in the upcoming years and reaffirming the global importance of base metal assets.

Merely bringing new mines into production won’t suffice to address the challenge of increasing net metal production for the energy transition. Ensuring a consistent and ample supply requires additional efforts. This surging copper demand sparks exploration of AI solutions to boost production, highlighting the pivotal role of technologies like that in this endeavor.

The Copper Challenge in Energy Transition

The International Energy Agency estimates that by 2040, essential mineral supply such as copper will need to rise sixfold to meet worldwide net-zero goals for battery manufacture. It’s a huge undertaking.

Customer implementation

Furthermore, according to the International Monetary Fund “the projected increase in metals consumption through 2050 under a net zero scenario, current production rates of graphite, cobalt, vanadium, and nickel appear inadequate, showing a more than two-thirds gap versus the demand. Current copper, lithium, and platinum supplies also are inadequate to satisfy future needs, with a 30-40 % gap versus demand.”

It may seem like an impossible task. We must mine more copper and other minerals if we are to save the earth from increased global warming. However, this endeavor often results in higher emissions and adverse impacts on the environment and local communities.

 

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.

How can Artificial Intelligence Boost Minerals Production?


Mining executives are increasingly looking to implement artificial intelligence (AI)-based technology to enhance production efficiency. They are also preparing for the future of their operations and change management.

These technologies, including digital twins, autonomous technologies, and deep learning neural networks, help uncover the hidden links between different mining process units and parameters, providing valuable insights into process performance.

Recent advancements in this field, such as the development of an integrated physics-informed machine learning model like IntelliSense.io’s Scientific AI, which can be deployed through a real-time software environment, help uncover hidden insights. This offers more accurate outcome predictions and promotes efficiency gains through real-time optimization when the data is fully utilized.

Customer implementation
In this Forbes Technology Council article by our Founder and CEO, Sam Bose, he greatly elaborates on the power of AI in boosting mineral production for the energy transition.

Sam explains, “Based on our earlier figures on copper mine production, a 3% to 5% increase in metal recovery using
AI applications would leverage our capacity to deliver an additional 450,000 tons per annum of copper worth $3.2 billion.  This is equal to the Las Bambas mine’s annual production capacity in Peru, a global top eight copper producer. Considering that the average mine takes 15 years to bring into production, improvements like this provide some air cover for an already suffocated industry”.

Interested in how Scientific AI Applications 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

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