Data analytics applied to the mining industry / Ali Soofastaei.
"The book describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centres, autonomous equipment and the opportunities offered by the industrial internet of things. It provides guidelines on how dat...
Saved in:
| Online Access: |
Full Text (via Taylor & Francis) |
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| Other Authors: | |
| Format: | eBook |
| Language: | English |
| Published: |
Boca Raton, FL :
CRC Press,
2021.
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| Edition: | 1st edition. |
| Subjects: |
| Summary: | "The book describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centres, 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. Each chapter ends with a section detailing lessons for mining. The final chapter explores the revised operating principles, the organizational characteristics and the new skills needed by mining companies"-- |
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| Physical Description: | 1 online resource (xvii, 253 pages) : illustrations (chiefly color) |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9780429433368 0429433360 9780429781759 042978175X 9780429781773 0429781776 0429781768 9780429781766 |
| Source of Description, Etc. Note: | Description based on online resource; title from digital title page (viewed on December 31, 2020) |
| Biographical or Historical Data: | 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 in-depth knowledge of Energy Efficiency Opportunities (EEO), VE and advanced data analysis. He is also proficient at using AI methods in data analysis to optimize the number of effective parameters in energy consumption in mining operations. Dr Soofastaei has been working in the oil, gas and mining industries and he has academic experience as an assistant professor. He has been in School of Mechanical and Mining Engineering at UQ since 2012 involved in many research and industrial projects, and I have been a member of the supervisory team for PhD and Master Students. Dr Soofastaei has completed many research projects and published their results in a lot of journal and conference papers. He also has developed few patents and five software packages. |