Advanced Analytics in Mining Engineering
Please note:
this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days).
Leverage Advanced Analytics in Mining Industry to Make Better Business Decisions
Author(s): Ali Soofastaei
Format: Hardback
Publisher: Springer Nature Switzerland AG, Switzerland
Imprint: Springer Nature Switzerland AG
ISBN-13: 9783030915889, 978-3030915889
Synopsis
In this book, Dr. Soofastaei and his colleagues reveal how all mining managers can effectively deploy advanced analytics in their day-to-day operations- one business decision at a time.
Most mining companies have a massive amount of data at their disposal. However, they cannot use the stored data in any meaningful way. The powerful new business tool-advanced analytics enables many mining companies to aggressively leverage their data in key business decisions and processes with impressive results.
From statistical analysis to machine learning and artificial intelligence, the authors show how many analytical tools can improve decisions about everything in the mine value chain, from exploration to marketing.
Combining the science of advanced analytics with the mining industrial business solutions, introduce the Advanced Analytics in Mining Engineering Book as a practical road map and tools for unleashing the potential buried in yourcompanys data.
The book is aimed at providing mining executives, managers, and research and development teams with an understanding of the business value and applicability of different analytic approaches and helping data analytics leads by giving them a business framework in which to assess the value, cost, and risk of potential analytical solutions. In addition, the book will provide the next generation of miners undergraduate and graduate IT and mining engineering students with an understanding of data analytics applied to the mining industry. By providing a book with chapters structured in line with the mining value chain, we will provide a clear, enterprise-level view of where and how advanced data analytics can best be applied. This book highlights the potential to interconnect activities in the mining enterprise better. Furthermore, the book explores the opportunities for optimization and increased productivity offered by better interoperability along the mining value chain in line with the emerging vision of creating a digital mine with much-enhanced capabilities for modeling, simulation, and the use of digital twins in line with leading digital industries.
