Skip to main content
SpringerLink
Log in

Advanced Analytics for Modern Mining

  • Chapter
  • First Online:
Advanced Analytics in Mining Engineering

  • 1132 Accesses

Abstract

Technology is growing very fast, and we are facing the Fourth Revolution in industry. Digital transformation has found its way in to many different traditional and modern industries. Digitalization and automation are two common words in mining these days. However, there are many challenges in the mining industry to reach the appropriate maturity level for Industry 4.0. Data collection systems, cloud-based storage, intelligent data architecture, creating online data hubs are some examples of digitalization challenges. Moreover, it is essential to use advanced analytics models applying artificial intelligence and machine learning models for automation, prediction, and optimization. Mine managers need an intelligent indigent virtual assistant to make better decisions and develop smart mines. This chapter some key components of intelligent mining and helps researchers understand Industry 4.0 in the mining context.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 159.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Ślusarczyk, B. 2018. Industry 4.0: Are we ready? Polish Journal of Management Studies 17.

    Google Scholar 

  2. Jurdziak, L., R. Błażej, and M. Bajda. 2018. Cyfrowa rewolucja w transporcie przenośnikowym–taśma przenośnikowa 4.0. Transport 2: 40.

    Google Scholar 

  3. Bongaerts, J.C. 2020. Mining 4.0 in the context of developing countries. African Journal of Mining, Entrepreneurship and Natural Resource Management (AJMENRM) 1 (2): 36–43.

    Google Scholar 

  4. Bartnitzki, T. 2017. Mining 4.0—Importance of Industry 4.0 for the raw materials sector. Artificial Intelligence 2: M2M.

    Google Scholar 

  5. Rylnikova, M., D. Radchenko, and D. Klebanov. 2017. Intelligent mining engineering systems in the structure of Industry 4.0. E3S Web of Conferences. EDP Sciences.

    Google Scholar 

  6. Lööw, J., L. Abrahamsson, and J. Johansson. 2019. Mining 4.0—The impact of new technology from a workplace perspective. Mining, Metallurgy & Exploration 36 (4): 701–707.

    Google Scholar 

  7. Roldán, J.J., et al. 2019. A training system for Industry 4.0 operators in complex assemblies based on virtual reality and process mining. Robotics and Computer-Integrated Manufacturing 59: 305–316.

    Google Scholar 

  8. Faz-Mendoza, A., et al. 2020. Intelligent processes in the context of Mining 4.0: Trends, research challenges, and opportunities. In 2020 International Conference on Decision Aid Sciences and Application (DASA). IEEE.

    Google Scholar 

  9. Soofastaei, A. 2020. Data analytics for energy efficiency and gas emission reduction. In Data analytics applied to the mining industry, 169–192. CRC Press.

    Google Scholar 

  10. Sishi, M., and A. Telukdarie. 2020. Implementation of Industry 4.0 technologies in the mining industry—A case study. International Journal of Mining and Mineral Engineering 11 (1): 1–22.

    Google Scholar 

  11. Nanda, N.K. 2019. Intelligent enterprise with Industry 4.0 for the mining industry. In International Symposium on Mine Planning & Equipment Selection. Springer.

    Google Scholar 

  12. Soofastaei, A. 2020. Digital transformation of mining. In Data analytics applied to the mining industry, 1–29. CRC Press.

    Google Scholar 

  13. Deloitte. 2018. The top 10 issues shaping mining in the year ahead. Tracking the trends 2018, July 3. Available from: https://www2.deloitte.com/content/dam/Deloitte/us/Documents/energy-resources/us-er-ttt-report-2018.pdf.

  14. Wang, L.G. 2015. Digital mining technology and upgrading of mine technology in China. World Non-Ferrous Metal 7–13.

    Google Scholar 

  15. Carter, R.A. 2014. Equipment selection is key for productivity in underground loading and haulage. Engineering and Mining Journal 215 (6): 46.

    Google Scholar 

  16. Li, J.-G., and K. Zhan. 2018. Intelligent mining technology for an underground metal mine based on unmanned equipment. Engineering 4 (3): 381–391.

    Article  Google Scholar 

  17. Gustafson, A., et al. 2014. Development of a Markov model for production performance optimization. Application for semi-automatic and manual LHD machines in underground mines. International Journal of Mining, Reclamation, and Environment 28 (5): 342–355.

    Google Scholar 

  18. Deloitte. 2018. Intelligent mining. Delivering real value, March 2018. Available from: https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Energy-and-Resources/gx-intelligent-mining-mar-2018.pdf.

  19. Deloitte. 2019. Intelligent mining. Delivering real value. For private circulation only, October 2019. Available from: https://www2.deloitte.com/content/dam/Deloitte/in/Documents/about-deloitte/in-mm-ntelligent-mining-brochure-noexp.pdf.

  20. Da Xu, L., W. He, and S. Li. 2014. Internet of Things in industries: A survey. IEEE Transactions on Industrial Informatics 10 (4): 2233–2243.

    Article  Google Scholar 

  21. Blanchet, M., et al. 2014. Industry 4.0: The new industrial revolution—How Europe will succeed, vol. 11, 2014. München: Hg. v. Roland Berger Strategy Consultants GmbH.

    Google Scholar 

  22. Schmidt, R., et al. 2015. Industry 4.0—Potentials for creating smart products: Empirical research results. In International Conference on Business Information Systems. Springer.

    Google Scholar 

  23. Anastasova, Y. Internet of Things in the mining industry—Security technologies in their application.

    Google Scholar 

  24. de Moura, R.L., L.D.L.F. Ceotto, and A. Gonzalez. 2017. Industrial IoT and advanced analytics framework: An approach for the mining industry. In 2017 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE.

    Google Scholar 

  25. Neubert, R. 2016. IIoT offers economical, operational benefits. Plant Engineering 4: 9–10. In Focus.

    Google Scholar 

  26. Clegg, S., M. Kornberger, and T. Pitsis. 2016. Administração e organizações: uma introdução à teoria e à prática. Bookman Editora.

    Google Scholar 

  27. Lala, A., et al. 2016. Productivity at the mine face: Pointing the way forward, 2–12. New York: McKinsey and Company.

    Google Scholar 

  28. Ng, E. 2013. Commodities super-cycle is ‘taking a break’: Runaway prices in commodities markets have ended, but long-term demand for commodities on the mainland is strong. South China Morning Press.

    Google Scholar 

  29. Li, Y., et al. 2012. Towards a theoretical framework of strategic decision, supporting capability and information sharing under the Internet of Things. Information Technology and Management 13 (4): 205–216.

    Article  Google Scholar 

  30. Velosa, A., Y. Natis, and B. Lheureux. 2016. Use the IoT platform reference model to plan your IoT business solutions, September 17. Available from: https://www.gartner.com/en/documents/3447218-use-the-iot-platform-reference-model-to-plan-your-iot-bu.

  31. Lee, I., and K. Lee. 2015. The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons 58 (4): 431–440.

    Article  Google Scholar 

  32. Gubbi, J., et al. 2013. Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems 29 (7): 1645–1660.

    Article  Google Scholar 

  33. Cooper, J., and A. James. 2009. Challenges for database management in the Internet of Things. IETE Technical Review 26 (5): 320–329.

    Article  Google Scholar 

  34. Abu-Elkheir, M., M. Hayajneh, and N.A. Ali. 2013. Data management for the Internet of Things: Design primitives and solution. Sensors 13 (11): 15582–15612.

    Article  Google Scholar 

  35. Aziz, A., O. Schelén, and U. Bodin. 2020. A study on industrial IoT for the mining industry: Synthesized architecture and open research directions. IoT 1 (2): 529–550.

    Article  Google Scholar 

  36. World Economic Forum & Accenture. 2017. Digital transformation initiative 2017. Cited 2021 Mar 20. Available from: https://www.accenture.com/t20170411t115809z__w__/us-en/_acnmedia/accenture/conversion-assets/wef/pdf/accenture-telecommunications-industry.pdf.

Download references

Author information

Authors and Affiliations

  1. Luleå University of Technology, Luleå, Sweden

    Diego Galar & Uday Kumar

  2. TECNALIA, Basque Research and Technology Alliance (BRTA), 48170, Derio, Spain

    Diego Galar

Authors
  1. Diego Galar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Uday Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Diego Galar .

Editor information

Editors and Affiliations

  1. Artificial Intelligence Center, Vale, WA, Australia

    Ali Soofastaei

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Galar, D., Kumar, U. (2022). Advanced Analytics for Modern Mining. In: Soofastaei, A. (eds) Advanced Analytics in Mining Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-91589-6_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-91589-6_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-91588-9

  • Online ISBN: 978-3-030-91589-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation