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- Author: Ali Soofastaei
- Publisher: CRC Press
- ISBN-10: 0367612240
- ISBN-13: 9780367612245
- Format: 15.6 x 23.4 x 1.5 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
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Description
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
EXTRA 10 % discount with code: EXTRA
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- Author: Ali Soofastaei
- Publisher: CRC Press
- ISBN-10: 0367612240
- ISBN-13: 9780367612245
- Format: 15.6 x 23.4 x 1.5 cm, softcover
- Language: English English
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
Reviews