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
The aim of the book is to provide practical help for executives, managers and research and development teams to identify where and how to apply advanced data analytics in mining engineering. Extensive case studies worked examples and details of how to develop and use an Analytics Maturity Matrix, and associated Analytics Roadmap has been provided.
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