The industrial revolution:- How Mining industries are adopting AI?! In industries such as mining, for profitability improving efficiency and enhancing productivity are very crucial. Even the minor improvements in yields or speed could make a big and extraordinary difference.
Moreover, the mining industry also indirectly impacts nearly every other industry, since it provides the raw material for almost every aspect of the economy. The major impact here is to be seen as, through AI many mining industries could create intelligent mining operations. Artificial intelligence is now a real game-changer for countless businesses and companies in the market.
Just a few years ago, artificial intelligence was a too technically advanced idea for the people to wonder how it would truly impact the world.
According to some experts, investment and technological development of AI are skyrocketing even at the rate, the world isn’t ready for. But now it has impacted so hard, that the companies in every sector continue to lead this way with this new technology, even with the uncertainties and mixed feelings.
Mineral exploration:-
The mineral exploration is basically the mass amount of data, in the form of soil samples, chip samples, geoChemistry, drill results, and essay results and each drill hole is a tiny snapshot of the processes that form the earth. Moreover, a single drill hole can create 200 megabytes of data but in case there are more drill holes including the other type of information, an exploration project can produce terabytes of data.
All of these points are so important because through this data we can find new mineral deposits, but to sort them would even be difficult even for many capable geologists.
But, by using machine learning we can train the computer to spot the areas showing similar patterns, which has been discovered in the past.
Artificial Intelligence and Machine Learning:-
AI and machine learning basically help mining companies find minerals to extract. And some companies are already involved in this like, Goldspot Discoveries Inc. which basically focuses on finding gold by using Artificial Intelligence or Machine Learning.
Autonomous Vehicles and Drillers:-
While many of us have been focusing on the progress, Uber, Google, and Tesla have made their mark with autonomous vehicles, Many people don’t have any clue that (Rio Tinto) is also considered to be one of the largest metals and mining corporations, has been using autonomous haul trucks since 2008, which carries around 350 tons and can independently operate. And it is essential to note that these trucks have been effective in reducing fuel use by 13 percent and are much safer to operate.
Safety:-
AI has the ability to help in mishappenings, for instance, help workers prevent accidents and injuries on the job, help mining engineers. Also, if we can collect high-quality data, the prediction of the failures could be easy, especially the failures that can not only affect production but could harm any workers nearby.
Moreover, in predicting failures, by analyzing patterns, we can use AI to predict other potential hazards as well. This could be helpful for the future because the mining environment could affect the operation and lifespan of the equipment.
In addition to it, we can constantly keep track of the health and performance of the equipment which is used by the industries, which greatly helps in eliminating the surprise failures and dangers to workers.
Development and Construction:-
Machine learning could also be used to answer the question like “how do we build a mine?”
Moreover, You can predict development and construction phases, aerial imagery, and mine site construction designs from the past. Having a large amount of data is what’s holding us back.
Security:-
Grateful to the Internet, because of which technology and sensors including mining equipment could now be monitored and maintained conveniently and effectively, even before breakdowns occur.
Sensors can easily monitor temperature, speed, and vibration on machines to take action which assists in transforming preventative maintenance into predictive maintenance.
Real-time data and analytics could also be assessed through AI Machine Learning so that mining operations can be safer for all involved.
Current Advancements:-
So far, in mineral exploration, Goldspot Discoveries is applying AI and Machine Learning. Recently they predicted 86% of existing gold deposits in the Canadian Abitibi gold belt, which they have achieved using geological, topographical and mineral data from 4% of the total surface area.
AI is also used by Motion Metrics’ Fragmentation Analysis to more accurately measure rock fragmentations. This method of data collection basically provides valuable feedback to the engineers also helps in enhancing and increasing productivity, and at times even optimizes teeth changeouts by monitoring teeth wear.
Tomra has also developed mineral and ore sorting equipment, which basically uses sensors to separate mineral ores from waste rock and even from things like fast-paced laser sorting and product recognition. To enable automated ore fragmentation assessment PETRA Data Science in general offers technology that uses machine learning AI.
Their algorithms use data collected from 3D mapping to assess ore fragmentation within a minute in comparison with manual processing which could consume more than an hour.
Final words:-
The uses of AI and automation have changed the phase of the mining industry by lowering and saving costs, increasing and enhancing efficiency and providing tons of other benefits to the companies.
However, more and more companies day by day are working on scaling the use of Machine Learning AI in mining, probably we could now start seeing the use of AI in the mining industry. AI is the Future. The fact that Machine Learning Artificial Intelligence has made its path across many industries, and mining stands to benefit greatly from its application. While machine learning has been perfected and the promise of tools means more efficiency and effectiveness and therefore more money for the people, especially in the mining industry.
