Authors: Ali Soofastaei
Volume: –
Issue: –
Date: 2018
Mining industry consumes a significant amount of energy and makes greenhouse gas emissions in various operations such as exploration, extraction, transportation and processing. A considerable amount of this energy and gas emissions can be reduced by better managing the operations. The mining method and equipment used mainly determine the type of energy source in any mining operation. In surface mining operations, mobile machines use diesel as a source of energy. These machines are haul trucks excavators, diggers and loaders, according to the production capacity and site layout and they use a considerable amount of fuel in surface mining operation; hence, the mining industry is encouraged to conduct some research projects on the energy efficiency of mobile equipment. Classical analytics methods that commonly used to improve energy efficiency and reduce gas emissions are not sufficient enough. The application of artificial intelligence and deep learning models are growing fast in different industries, and this is a new revolution in the mining industry. In this chapter, the application of artificial intelligence methods to reduce the gas emission in surface mines with some case studies will be explained.
Subscribe to our newsletter so we can send you offers, discounts, and articles.
Soofastaei-Publications (SP) is a newly founded global publisher that produces specialized and high-quality books and e-books and holds world-class conferences and webinars.
This organization is a part of Soofastaei Institute, which provides technical business solutions, publications, and educational services in advanced analytics and AI in various industries.
Responses