The Global Mining Industry has been suffering under the pressure of falling commodity prices. The industry is at an inflection point where companies must unlock new disruptive technologies to enhance its productivity. Companies must adopt these technologies to survive and compete in the longer horizon. Artificial Intelligence (AI) is one such emerging technology which has the power to transform the Mining Industry. It helps the industry to transcend the traditional descriptive methodologies and pave into a future digital state which boasts of trends like machine- learning prediction, autonomous techniques, etc.
AI is a key strategic technology trend which is going to disrupt many business models in future. Gartner predicts that "by 2020, AI will be a top five investment priority for more than 30 percent of CIOs."1 Mining companies in the coming years must adapt and adopt AI in their digital maturity journey to be more productive and efficient across their value chain. AI finds its applicability across multiple business functions throughout the mining value chain like Mining Operations, Logistics, Exploration, etc. AI-powered robotic devices can perform core operation activities like drilling, blasting, loading, hauling, etc.
AI applicability across Mine Value Chain
AI application's relevance extends from exploration to the market stage of the value chain. Let us look at some industry use cases for these artificial intelligence applications.
- Geotechnical assessment in open-pit & underground operations
Geotechnical assessment is utilizing machine learning via advanced fragmentation algorithms for automatic assessment within a short interval of time. These AI powered algorithms remove the manual processing done by geotechnical engineers. The 3D mapping data is passed through machine learning algorithms to recognize spalling, cracked shotcrete, plate deformation & mesh bagging.
- AI powered autonomous equipment
AI finds its applicability in the autonomous operation of heavy equipments operating in mines across the globe. The existing technologies in Fleet Management systems is limited to use of GPS and few sensors like LiDAR. AI powered autonomous vehicles augments the conventional features by combining the sensor inputs with the deep learning AI systems to enable safe routing of vehicles in real time with increased accuracy and precision. AI driven autonomous vehicles will also eliminate the risk of safety hazards caused by human drivers due to fatigue, etc. The success of the AI powered vehicles lies with AI system trained on a humongous data pool of potential situations that might occur in real life. The system must be capable and robust enough to handle unexpected situations.
- AI enabled solutions for Procurement
Traditional procurement solutions face challenges to tackle issues like long sourcing lead times, increasing regulations, vendor multiplicity, third-party supplier risks, etc. AI solutions help to minimize these risk through solutions like Virtual Advisory agents which aid in taking strategic decisions like spot buying, supplier selection & category management. These advisory agents classify the suppliers into risk profiles through algorithms developed from various supplier data. These agents also equipped also to handle transactional activities like service desk, conducting a request for proposals, etc.
Mining companies must adapt to industry-specific artificial intelligence applications for addressing the industry pain points and stay ahead of the peers. For this, the companies should bring about a cultural change to realign its workforce to changing technologies and align all its stakeholders to seamlessly embrace digital practices in the organization for digital transformation of the customer experience in the years ahead.
1 Gartner, How Enterprise Software Providers Should (and Should Not) Exploit the AI Disruption, July 2017