Intelligent industry technologies applied to condition monitoring techniques in mining equipment: A systematic review

Abstract

The mining industry has historically been one of the pillars of the global economy; however, its nature presents unique challenges regarding Asset Management. With the consolidation of the Fourth Industrial Revolution, new opportunities have arisen to enhance the performance of operations and maintenance activities, such as equipment condition monitoring. This article aims to characterize the smart industry technologies used in condition monitoring techniques for mining equipment. A systematic literature review was conducted using databases such as Scopus and Web of Science, applying inclusion and exclusion criteria to select relevant studies. The results indicate that the most commonly used technologies are Machine Learning, IoT, Big Data, and sensors, applied to equipment such as conveyor belts, trucks, shovels, and crushers. These technologies improve fault detection accuracy, maintenance planning, and operational safety. This article aims to be a theoretical reference for future research and for mining companies interested in adopting these technologies.