In 2019, the global size of mining equipment was USD 144.37 billion and was projected to increase by 12.7% from 2020 to 2027, at a composite annual growth rate (CAGR). The main aspects of mining will continue to be modified over the coming years by ongoing digital mining innovation. In the forecasted era, increased investment and funding from the government for digital mine innovations are expected to trigger demand for mining equipment. Improvements and advances in ore grade extraction methods and equipment have helped enhance the life of older mines.
A recent review of the technology usage of the mining sector has shown that it allows the industry to comply with environmental and social responsibility policies. Mining companies are responsible for ensuring that their environmental impact is minimised and the soil is rehabilitated in its natural state over the lifespan. This can be costly and error prone with suboptimal processing and review of data when performed by hand-operated processes.
The industry is currently harnessing less than 3 percent of the data from equipment because it rarely reaches experts in good time for evaluation and determination. By being able to collect more data points simultaneously from many sensors and using the cumulative data sets, the health of equipment can be calculated and future faults can be predicted accordingly. The correct use of technology can lead to performance, fault and inactivity prevention and productivity prediction in this field.
For the survival of modern society, metal materials are critical. This industry would have difficulties in meeting the industry’s goals without an advanced automated mining solution. M2M with artificial intelligence and predictive analysis is essential to its growth. Its industrial network of objects is IIoT and machine for machine training. The industry has been calling for this kind of innovation since a long time. It has already taken advantage of technology and is gaining recognition. The end-to-end technology platform that supports the mining industry in the real-time linkage to and analysis of data, and then uses the learning, to forecast an outcome, to eventually act on the data, with multiple computers, controllers and sensors is the need of the hour. It enables the industry to make decisions in real time, to reduce fault with equipment, to increase protection, to minimise downtime and to reduce waste, and to deliver end-to-end automation.
