Advanced Analytics In Mining Engineering
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Advanced Analytics In Mining Engineering
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Author : Ali Soofastaei
language : en
Publisher:
Release Date : 2022
Advanced Analytics In Mining Engineering written by Ali Soofastaei and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
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.
Advanced Analytics In Mining Engineering
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Author : Ali Soofastaei
language : en
Publisher: Springer Nature
Release Date : 2022-02-23
Advanced Analytics In Mining Engineering written by Ali Soofastaei and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-23 with Business & Economics categories.
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 Analytics Applied To The Mining Industry
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Author : Ali Soofastaei
language : en
Publisher: CRC Press
Release Date : 2020-11-12
Data Analytics Applied To The Mining Industry written by Ali Soofastaei and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-12 with Computers categories.
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
Coal Preparation Technique In Mining Engineering
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Author : Prof. Dr. Bilal Semih Bozdemir
language : en
Publisher: Prof. Dr. Bilal Semih Bozdemir
Release Date :
Coal Preparation Technique In Mining Engineering written by Prof. Dr. Bilal Semih Bozdemir and has been published by Prof. Dr. Bilal Semih Bozdemir this book supported file pdf, txt, epub, kindle and other format this book has been release on with Technology & Engineering categories.
Coal Preparation Technique in Mining Engineering Introduction to Coal Preparation Importance of Coal Preparation in Mining Historical Development of Coal Preparation Coal Formation and Composition Coal Classification based on Rank Coal Characterization and Analysis Sampling and Handling of Coal Coal Preparation Process Overview Comminution: Crushing and Grinding Size Reduction Principles and Equipment Screening and Classification Techniques Gravity Separation: Dense Media Separation Gravity Separation: Jigging and Tabling Froth Flotation for Fine Coal Cleaning Dewatering and Thermal Drying Techniques Environmental Considerations in Coal Preparation Water Management in Coal Preparation Plants Coal Preparation Plant Design Factors Plant Layout and Equipment Arrangement Automation and Control Systems in Coal Prep Maintenance and Optimization Strategies Coal Fines Utilization and Beneficiation Coal Slurry Transportation and Disposal Safety and Health Aspects in Coal Prep Regulatory Compliance in Coal Preparation Emerging Technologies in Coal Preparation Dry Coal Separation Techniques Advanced Sensor-based Sorting Methods Coal Preparation Economics and Feasibility Supply Chain and Logistics Management Sustainability and Environmental Impacts Global Trends in Coal Preparation Case Studies of Successful Coal Prep Plants Challenges and Future Research Directions Integrated Approach to Coal Beneficiation Conclusion and Key Takeaways
Data Analytics Applied To The Mining Industry
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Author : Ali Soofastaei
language : en
Publisher: CRC Press
Release Date : 2020-11-12
Data Analytics Applied To The Mining Industry written by Ali Soofastaei and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-12 with Computers categories.
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
Machine Learning In Geohazard Risk Prediction And Assessment
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Author : Biswajeet Pradhan
language : en
Publisher: Elsevier
Release Date : 2025-07-01
Machine Learning In Geohazard Risk Prediction And Assessment written by Biswajeet Pradhan and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Science categories.
Machine Learning in Geohazard Risk Prediction and Assessment: From Microscale Analysis to Regional Mapping presents an overview of the most recent developments in machine learning techniques that have reshaped our understanding of geo-materials and management protocols of geo-risk. The book covers a broad category of research on machine-learning techniques that can be applied, from microscopic modeling to constitutive modeling, to physics-based numerical modeling, to regional susceptibility mapping. This is a good reference for researchers, academicians, graduate and undergraduate students, professionals, and practitioners in the field of geotechnical engineering and applied geology. - Introduces machine-learning techniques in the risk management of geo-hazards, particularly recent developments - Covers a broader category of research and machine-learning techniques that can be applied, from microscopic modeling to constitutive modeling, to physics-based numerical modeling, to regional susceptibility mapping - Contains contributions from top researchers around the world, including authors from the UK, USA, Australia, Austria, China, and India
Mining Engineering And Topography
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Author :
language : en
Publisher: Bilal Semih Bozdemir
Release Date :
Mining Engineering And Topography written by and has been published by Bilal Semih Bozdemir this book supported file pdf, txt, epub, kindle and other format this book has been release on with Architecture categories.
As we navigate the challenges posed by fluctuating market demands, environmental regulations, and community expectations, effective site monitoring emerges as an indispensable aspect of sustainable mining practices. The harmonization of geotechnical, hydrological, air quality, and noise monitoring provides a comprehensive approach to identifying potential hazards, thereby facilitating timely interventions and optimizing resource management.
Underground Production Methods In Mining Engineering
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Author : Prof. Dr. Bilal Semih Bozdemir
language : en
Publisher: Prof. Dr. Bilal Semih Bozdemir
Release Date :
Underground Production Methods In Mining Engineering written by Prof. Dr. Bilal Semih Bozdemir and has been published by Prof. Dr. Bilal Semih Bozdemir this book supported file pdf, txt, epub, kindle and other format this book has been release on with Technology & Engineering categories.
Underground Production Methods in Mining Engineering Introduction to Underground Mining Advantages of Underground Mining Challenges of Underground Mining Shaft Mining Drift Mining Slope Mining Room-and-Pillar Mining Longwall Mining Safety Considerations in Underground Mining Ventilation Systems in Underground Mines Ground Support Techniques Drilling and Blasting Techniques Transportation Systems in Underground Mines Automation and Robotics in Underground Mining
Mining Machinery In Mining Engineering
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Author : Prof. Dr. Bilal Semih Bozdemir
language : en
Publisher: Prof. Dr. Bilal Semih Bozdemir
Release Date :
Mining Machinery In Mining Engineering written by Prof. Dr. Bilal Semih Bozdemir and has been published by Prof. Dr. Bilal Semih Bozdemir this book supported file pdf, txt, epub, kindle and other format this book has been release on with Technology & Engineering categories.
Mining Machinery in Mining Engineering Introduction to Mining Machinery Historical Overview of Mining Machinery Types of Mining Machinery Surface Mining Machinery Underground Mining Machinery Drill Rigs and Excavators Hauling and Loading Machinery Crushing and Grinding Equipment Mineral Processing Machinery Continuous Mining Machines Longwall Mining Machinery Maintenance and Repair of Mining Machinery Safety Considerations in Mining Machinery Environmental Impact of Mining Machinery Advancements in Mining Machinery Technology Automation and Robotics in Mining Machinery Hydraulic and Pneumatic Systems in Mining Machinery Electrical and Control Systems in Mining Machinery Fuel-Efficient Mining Machinery Noise and Vibration Reduction in Mining Machinery Remote Controlled Mining Machinery Maintenance Strategies for Mining Machinery Condition Monitoring of Mining Machinery Predictive Maintenance in Mining Machinery Supply Chain and Logistics for Mining Machinery Cost-Effective Ownership of Mining Machinery Leasing and Rental Options for Mining Machinery Operator Training and Certification for Mining Machinery Regulatory Compliance and Certifications for Mining Machinery Sustainability and Eco-friendly Mining Machinery Innovations in Mining Machinery Design 3D Printing and Additive Manufacturing in Mining Machinery Internet of Things (IoT) and Mining Machinery Big Data Analytics for Mining Machinery Artificial Intelligence in Mining Machinery Virtual and Augmented Reality in Mining Machinery Cybersecurity Considerations for Mining Machinery Future Trends and Challenges in Mining Machinery Case Studies: Successful Mining Machinery Applications Industry Partnerships and Collaborations in Mining Machinery Conclusion: The Evolving Role of Mining Machinery
Advanced Analytics And Artificial Intelligence Applications
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Author : Ali Soofastaei
language : en
Publisher: BoD – Books on Demand
Release Date : 2019-11-13
Advanced Analytics And Artificial Intelligence Applications written by Ali Soofastaei and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-13 with Computers categories.
Computers and machines were developed to reduce time consumption and manual human efforts to complete projects efficiently. With fast-growing technologies in the field, we have finally reached a stage where almost everyone in the world has access to these high technologies. However, this is just a starting phase because future development is taking a more advanced route in the shape of artificial intelligence (AI). Although AI is under the computer science umbrella, nowadays there is no field unaffected by this high technology. The overall aim of using intelligence learning methods is to train machines to think intelligently and make decisions in different situations the same as humans. Previously, machines were doing what they were programmed to do, but now with AI, devices can think and behave like a human being. This book aims to present the application of advanced analytics and AI in different industries as practical tools to develop prediction, optimization, and make decision models.