Data Analytics Applied to the Mining Industry
Seiten
2023
CRC Press (Verlag)
978-0-367-61224-5 (ISBN)
CRC Press (Verlag)
978-0-367-61224-5 (ISBN)
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.
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
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
1. Digital Transformation of Mining. 2. Data Analytics and the Mining Value Chain. 3. Data Collection, Storage and Retrieval. 4. Making Sense of Data. 5. Analytics Toolset. 6. Making Decisions based on Analytics. 7. Process Performance Analytics. 8. Process Maintenance Analytics. 9. Data Analytics for Energy Efficiency and Gas Emission Reduction. 10. Future Skills Requirements.
| Erscheinungsdatum | 28.09.2023 |
|---|---|
| Zusatzinfo | 20 Tables, black and white; 150 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 156 x 234 mm |
| Gewicht | 453 g |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Mathematik / Informatik ► Informatik ► Theorie / Studium | |
| Technik ► Bauwesen | |
| Technik ► Bergbau | |
| Wirtschaft ► Volkswirtschaftslehre | |
| ISBN-10 | 0-367-61224-0 / 0367612240 |
| ISBN-13 | 978-0-367-61224-5 / 9780367612245 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
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