As legacy technologies fail to keep up with the growing demand for advanced mining activities for increased outputs and greater profits, management consulting company GlobalData believes artificial intelligence (AI) can help.
The company says AI can make mining companies more productive and profitable with insights-led decisions across the value chain.
“Mining leaders must adopt AI and its relevant technologies like machine learning (ML) and deep learning (DL) to turn challenges into opportunities with data-driven insights that can help them with several aspects of mining activities ranging from ore exploration to extraction, and mineral processing to marketing,” GlobalData senior disruptive tech analyst Abhishek Paul Choudhury says.
GlobalData’s latest Innovation Radar report titled ‘Digital mine: how technology is transforming mining from prospecting to reclamation Volume 2’ highlights how AI-related solutions are improving processes across the mining sector value chain.
Australian software company Datarock introduced the Datarock Core platform that leverages DL to automate the extraction of geological information from imagery and videos. The platform allows users to upload imagery and apply various general or custom deep learning models to analyse the data for quality assurance and quality check purposes, and to extract various important types of geological and geotechnical information.
German chemical company BASF partnered with British AI startup IntelliSense.io to develop the BASF Intelligent Mine solution, which can help mining companies make their operations safe, efficient and sustainable. With both on-site and cloud deployment features, it offers optimisation-as-a-service to help mine operators predict and simulate the future performance of a mining site and obtain process-specific recommendations.
Additionally, Australian mining equipment provider MineWare has rolled out an AI-powered drill automation platform named Phoenix AI that helps mining companies with the optimisation of blast-hole drill operations. This can reduce poor hole quality and machine stress to eliminate the need to tune operational parameters on the machine with continuous monitoring and action-oriented insights.
Meanwhile, US technology startup Akkio introduced a forecasting solution for the mining sector to help forecast commodity prices and plan business accordingly. It uses AI and ML to access historic data on commodity prices and sales volume to simplify forecasting mineral commodities with models that can be deployed through an application programming interface, software platforms such as Zapier or Salesforce, or other web applications.
“AI and related applications can bring tangible benefits and are already showing improvements in mining business outcomes. It is safe to comment that there will be more AI-based developments to catalyse data-augmented optimal business decisions for the mining sector,” Choudhury says.