What does the adoption of Machine Learning, Artificial Intelligence and Big Data really mean in the mining industry?

Since its inception, the implementation of technological solutions has become a key element to improve processes in the mining industry, characterized by its constant modernization and changes. This is why the application of Machine Learning and Artificial Intelligence are key innovations to improve information collection and selection processes, as well as facilitate field activities, such as avoiding content loss.

Currently, the implementation of tools based on robotization and digital processes in the mining world bring efficiency to the processes and, at the same time, is a great help in caring for field personnel. “Artificial Intelligence is a great contribution to the protection of people in the works, since the process becomes more autonomous supported by technology. This is why the mining of the future will base work on telematics, which will allow more controlled and calculated environments as much as possible, where communications and obtaining information from the site (video, metrics, etc.) will become fundamental ”, explains Samuel Ramírez, Director of Hikvision Chile Projects.

Indeed, the benefits that the incorporation of certain technological tools can generate have a direct impact on cost reduction. “The highest return on investment achieved in the mining business is the product of the technologies that are applied to the different processes in the value chain. These technological adaptations that are developed in the mining process are linked with standards and interoperability capabilities. Both technological standards and interoperability are what support the different automation, robotics and control monitoring technologies so that they can maximize the contribution they generate, both safety and productivity indicators, trying to push it to increase its effectiveness using these capabilities. of compatibility”, assures José Fuentealba, Sales Manager of InterSystems LATAM.

Currently, there is an important use of Big Data information in predictive processes, where some of them are seeking to support such relevant values ​​as, for example, the monitoring of slopes in pits. This situation makes it possible to react quickly to small movements and thus anticipate the possibility of a sudden collapse. This is why “companies have put their efforts into collecting information and with it, being able to predict the failures of certain processes, in such a way as to be able to react earlier and obtain more time to deal with problems. Also, the use of technology has been incorporated in the form of predictive algorithms based on Machine Learning, applied to potentially risky aspects, protecting the health and safety of employees and using technology to predict incidents of drowsiness or fatigue, based on conditions. specific and in real time that can affect people”, adds the InterSystems executive.

Although there are several elements that have been incorporated or consolidated in the mining industry, automation and robotization have taken the lead in recent times. That is why, in order to continue incorporating this tool into the mining process, “It is essential to identify which processes of the mining operation are likely to introduce automation and robotization and apply a new digital model process. In addition, we must ensure the collection of data so that they are validated and finally have a mathematical model that is an instrument capable of processing this information and generating a result for better decision-making”, says Mauricio Andonie, sales manager of the Resources vertical. Natural and Mining of Adexus.

However, there are still pending technological issues for business processes to be truly digital. “In order to achieve these advances, there are still some challenges to be addressed, such as the importance of the interoperability of technological components, so that the entire production system works correctly, ensuring operational continuity and that the computing environments in development in the cloud are duly protected. for good cybersecurity”, concludes Andonie.