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Data Analytics Applied to the Mining Industry describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centers, autonomous equipment and the opportunities offered by the industrial internet of things. It provides guidelines on how data needs to be collected, stored and managed to enable the different advanced data analytics methods to be applied effectively in practice, through use of case studies, and worked examples. Aimed at graduate students, researchers, and professionals in the industry of mining engineering, this book: Explains how to implement advanced data analytics through case studies and examples in mining engineering Provides approaches and methods to improve data-driven decision making Explains a concise overview of the state of the art for Mining Executives and Managers Highlights and describes critical opportunity areas for mining optimization Brings experience and learning in digital transformation from adjacent sectors
|Publication date:||28th October 2020|
|Author:||Ali (The University of Queensland, Australia) Soofastaei|
|Publisher:||CRC Press an imprint of Taylor & Francis Ltd|
|Categories:||Mining industry, Mining industry, Mining industry, Databases, Mining industry, Mining industry,|
Ali Soofastaei is a Data Analyst at Vale and a Professorial Research Fellow at the University of Queensland (UQ) Australia. Vale is a Brazilian multinational corporation engaged in metals and mining and one of the largest logistics operators in Brazil. Vale is the most significant producer of iron ore and nickel in the world. Dr Soofastaei uses new models based on Artificial Intelligence (AI) methods to increase productivity, energy efficiency and reduce the total costs of mining operations. In the past 14 years, Dr Soofastaei has conducted a variety of research studies in academic and industrial environments. He has acquired an ...More About Ali (The University of Queensland, Australia) Soofastaei