Advanced Analytics in Mining Engineering Volume II

The first Volume of this book received an enthusiastic reception from researchers and is currently being prepared. However, due to the great response and new requests to add new topics to the book and due to new requests to collaborate with new content in previous chapters, the Advanced analytics for mining engineers Volume II became available so that those interested could participate in this project.

The book aims to provide practical help for executives, managers, and research and development teams to identify where and how to apply advanced data analytics in their enterprises. The use of advanced data analytics can support Their goals of improving energy efficiency, productivity, and reducing the associated costs of maintaining their mining operations.

The book is aimed at providing mining executives 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 analytic solutions. In addition, the book will provide the next generation of miners – undergraduate and graduate students of IT and mining engineering – 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 (ADA) can best be applied. In particular, we highlight the potential to interconnect activities in the mining enterprise better. We explore 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 like automotive and aerospace.