LEADER 05983nam 22007455 450 001 9910548170803321 005 20251202151134.0 010 $a9783030915896 010 $a3030915891 010 $z9783030915896 024 7 $a10.1007/978-3-030-91589-6. 035 $a(OCoLC)1308505835 035 $a(OCoLC)on1308505835 035 $aon1308505835 035 $a(MiAaPQ)EBC6896972 035 $a(PPN)260831948 035 $a(CKB)21325602900041 035 $a(BIP)83380657 035 $a(DE-He213)978-3-030-91589-6 035 $a(EXLCZ)9921325602900041 100 $a20220223d2022 u| 0 101 0 $aeng 135 $aurnn#|mamaa|| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAdvanced Analytics in Mining Engineering $eLeverage Advanced Analytics in Mining Industry to Make Better Business Decisions /$fedited by Ali Soofastaei 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (XIII, 747 p. 337 illus., 215 illus. in color. :)$conline resource 327 $aAdvanced analytics for mining industry.-Advanced analytics for modern mining.-Advanced analytics for ethical considerations in mining industry -- Advanced analytics for mining method selection -- Advanced analytics for valuation of mine prospects and mining projects -- Advanced analytics for mine exploration.-Advanced analytics for surface mining -- Advanced analytics for surface extraction -- Advanced analytics for surface mines planning -- Advanced analytics for dynamic programming -- Advanced analytics for drilling and blasting -- Advanced analytics for rock fragmentation -- Advanced analytics for rock blasting and explosives engineering in mining -- Advanced analytics for rock breaking -- Advanced analytics for mineral processing -- Advanced analytics for decreasing greenhouse gas emissions in surface mines -- Advanced analytics for Haul Trucks energy-efficiency improvement in surface mines -- Advanced analytics for mine materials handling -- Advanced analytics for mine materials transportation -- Advanced analytics for energy-efficiency improvement in mine-railway operation -- Advanced analytics for hard rock violent failure in underground excavations -- Advanced analytics for heat stress management in underground mines -- Advanced analytics for autonomous underground mining -- Advanced analytics for spatial variability of rock mass properties in underground mines. 330 $aIn 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 yourcompany?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. 606 $aOperations research 606 $aManagement science 606 $aData mining 606 $aIndustrial engineering 606 $aProduction engineering 606 $aMathematical models 606 $aComputer science 606 $aOperations Research, Management Science 606 $aData Mining and Knowledge Discovery 606 $aIndustrial and Production Engineering 606 $aMathematical Modeling and Industrial Mathematics 606 $aComputer Science 615 0$aOperations research. 615 0$aManagement science. 615 0$aData mining. 615 0$aIndustrial engineering. 615 0$aProduction engineering. 615 0$aMathematical models. 615 0$aComputer science. 615 14$aOperations Research, Management Science. 615 24$aData Mining and Knowledge Discovery. 615 24$aIndustrial and Production Engineering. 615 24$aMathematical Modeling and Industrial Mathematics. 615 24$aComputer Science. 676 $a622.028 676 $a622.0285 702 $aSoofastaei$b Ali 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910548170803321 996 $aAdvanced Analytics in Mining Engineering$92789032 997 $aUNINA