Statistics for Mining Engineering

Statistics for Mining Engineering PDF Author: Jacek M. Czaplicki
Publisher: CRC Press
ISBN: 1315815036
Category : Mathematics
Languages : en
Pages : 288

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Book Description
Many areas of mining engineering gather and use statistical information, provided by observing the actual operation of equipment, their systems, the development of mining works, surface subsidence that accompanies underground mining, displacement of rocks surrounding surface pits and underground drives and longwalls, amongst others. In addition, th

Statistics for Mining Engineering

Statistics for Mining Engineering PDF Author: Jacek M. Czaplicki
Publisher: CRC Press
ISBN: 1315815036
Category : Mathematics
Languages : en
Pages : 288

Get Book

Book Description
Many areas of mining engineering gather and use statistical information, provided by observing the actual operation of equipment, their systems, the development of mining works, surface subsidence that accompanies underground mining, displacement of rocks surrounding surface pits and underground drives and longwalls, amongst others. In addition, th

Statistics for Mining Engineering

Statistics for Mining Engineering PDF Author: Jacek M. Czaplicki
Publisher: CRC Press
ISBN: 1138001139
Category : Mathematics
Languages : en
Pages : 290

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Book Description
Many areas of mining engineering gather and use statistical information, provided by observing the actual operation of equipment, their systems, the development of mining works, surface subsidence that accompanies underground mining, displacement of rocks surrounding surface pits and underground drives and longwalls, amongst others. In addition, the actual modern machines used in surface mining are equipped with diagnostic systems that automatically trace all important machine parameters and send this information to the main producer’s computer. Such data not only provide information on the technical properties of the machine but they also have a statistical character. Furthermore, all information gathered during stand and lab investigations where parts, assemblies and whole devices are tested in order to prove their usefulness, have a stochastic character. All of these materials need to be developed statistically and, more importantly, based on these results mining engineers must make decisions whether to undertake actions, connected with the further operation of the machines, the further development of the works, etc. For these reasons, knowledge of modern statistics is necessary for mining engineers; not only as to how statistical analysis of data should be conducted and statistical synthesis should be done, but also as to understanding the results obtained and how to use them to make appropriate decisions in relation to the mining operation. This book on statistical analysis and synthesis starts with a short repetition of probability theory and also includes a special section on statistical prediction. The text is illustrated with many examples taken from mining practice; moreover the tables required to conduct statistical inference are included.

Advanced Analytics in Mining Engineering

Advanced Analytics in Mining Engineering PDF Author: Ali Soofastaei
Publisher: Springer Nature
ISBN: 3030915891
Category : Business & Economics
Languages : en
Pages : 746

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Book Description
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 your company’s 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.

Data Mining for Scientific and Engineering Applications

Data Mining for Scientific and Engineering Applications PDF Author: R.L. Grossman
Publisher: Springer Science & Business Media
ISBN: 1461517338
Category : Computers
Languages : en
Pages : 608

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Book Description
Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.

Geostatistics with Data of Different Support Applied to Mining Engineering

Geostatistics with Data of Different Support Applied to Mining Engineering PDF Author: Marcel Antonio Arcari Bassani
Publisher: Springer Nature
ISBN: 3030801934
Category : Science
Languages : en
Pages : 75

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Book Description
This book explains the integration of data of different support in Geostatistics. There is a common misconception in the mining industry that the data used for estimation/simulation should have the same size or support. However, Geostatistics provides the tools to integrate several types of information that may have different support. This book aims to explain these geostatistical tools and provides several examples of applications. The book is directed for a broad audience, including engineers, geologists, and students in the area of Geostatistics.

Data Analytics Applied to the Mining Industry

Data Analytics Applied to the Mining Industry PDF Author: Ali Soofastaei
Publisher: CRC Press
ISBN: 0429781776
Category : Computers
Languages : en
Pages : 273

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Book 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

Introductory Mining Engineering

Introductory Mining Engineering PDF Author: Howard L. Hartman
Publisher: John Wiley & Sons
ISBN: 9780471348511
Category : Technology & Engineering
Languages : en
Pages : 586

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Book Description
An introductory text and reference on mining engineering highlighting the latest in mining technology Introductory Mining Engineering outlines the role of the mining engineer throughout the life of a mine, including prospecting for the deposit, determining the site's value, developing the mine, extracting the mineral values, and reclaiming the land afterward. This Second Edition is written with a focus on sustainability-managing land to meet the economic and environmental needs of the present while enhancing its ability to also meet the needs of future generations. Coverage includes aboveground and underground methods of mining for a wide range of substances, including metals, nonmetals, and fuels. Completely up to date, this book presents the latest information on such technologies as remote sensing, GPS, geophysical surveying, and mineral deposit evaluation, as well as continuous integrated mining operations and autonomous trucks. Also included is new information on landscape restoration, regional planning, wetlands protection, subsidence mitigation, and much more. New chapters include coverage of: * Environmental responsibilities * Regulations * Health and safety issues Generously supplemented with more than 200 photographs, drawings, and tables, Introductory Mining Engineering, Second Edition is an indispensable book for mining engineering students and a comprehensive reference for professionals.

Statistical Methods for Mineral Engineers -

Statistical Methods for Mineral Engineers - PDF Author: Tim Napier-Munn
Publisher:
ISBN: 9780980362244
Category : Mining engineering
Languages : en
Pages : 627

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Book Description
Written by a mineral engineer for mineral engineers, and packed with real world examples, this book de-mystifies the statistics that most of us learned at university and then forgot. It shows how simple statistical methods, most of them available in Excel, can be used to make good decisions in the face of experimental uncertainty. Written in accessible language, it explains how experimental uncertainty arises from the normal measurement errors and how statistics provides a powerful methodology to manage that uncertainty. It assumes only that the readers are numerate, can use Excel, and want to do a better professional job. It is aimed squarely at mineral engineers and allied professionals (such as chemists) on the mine site, in head office, in engineering and supply companies and in universities. Most of the examples are illustrated in Excel but Minitab is also used for advanced techniques. The book includes over 100 Excel and Minitab hints. Example spreadsheets can be downloaded from the JKMRC and JKTech websites.

Data Analytics Applied to the Mining Industry

Data Analytics Applied to the Mining Industry PDF Author: Ali Soofastaei
Publisher: CRC Press
ISBN: 0429781768
Category : Computers
Languages : en
Pages : 232

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Book 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

Statistical Methods for Mineral Engineers

Statistical Methods for Mineral Engineers PDF Author: T. J. Napier-Munn
Publisher:
ISBN:
Category : Mineral engineering
Languages : en
Pages : 627

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Book Description