Human-Machine Collaboration in Mining: A Critical Review of Emerging Frontiers of Intelligence Systems in the Mining Industry

Details

• Journal Article:
  The Extractive Industries and Society
• Personal Author:
  Osei, Rosebella ; Frimpong, Samuel ; Venkat, Allada
• Description:
  Artificial Intelligence (AI) is driving significant transformations in numerous industries revolutionizing business processes, relationships, and engagements among individuals within organizations as well as with external service providers. These emerging smart technologies will also revolutionize the mining industry in significant ways. The future of AI in the mining industry will focus on autonomous equipment, drones and robots replacing humans in tasks performance. Mine automation is creating a new paradigm where technically savvy personnel are performing remote operations with improved workplace safety, health, and efficiencies. This study reviews the progress of mine automation, robotics, and other intelligent systems in the mining industry. We applied the technology, organization, and environment (TOE) framework to synthesize the various barriers associated with the implementation of these smart technologies in the various mining lifecycles. Using a preliminary literature review approach, we discuss enabling technologies facilitating human-machine collaboration along the mining life cycle, their impacts and synthesize the future of an industry where human and machine collaborate successfully to the benefit of humans. This review contributes to the best practices for managing change as an enabling factor to facilitate the smooth implementation of smart technologies in the mining industry. Description provided by NIOSH
• Subjects:
  • Automation
  • Mining
  • Occupational Health
  • Robotics
  • Safety
• Keywords:
  • Mining industry
  • Artificial intelligence
  • Automation
  • Emerging technology
  • Robotics
  • Mining equipment
  • Mining engineering
  • Author Keywords: Human-machine collaboration
  • Artificial intelligence
  • Smart technologies
  More +
• ISSN:
  2076-3417
• Document Type:
  Text
• Funding:
  Cooperative Agreement
• Genre:
  Journal Article
• Place as Subject:
  Kansas City Region OSHA ; Missouri
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  14 pdf pages
• Volume:
  24
• NIOSHTIC Number:
  nn:20071750
• Citation:
  Extr Ind Soc 2025 Dec; 24:101746
• Contact Point Address:
  Rosebella Osei, Engineering Management and Systems Engineering, Missouri University of Science and Technology, 600 W 14th Street, Rolla MO, 65409
• Email:
  rodpn@mst.edu
• Federal Fiscal Year:
  2026
• NORA Priority Area:
  Mining
• Performing Organization:
  Missouri University of Science and Technology
• Peer Reviewed:
  True
• Start Date:
  2023/09/01
• End Date:
  2027/08/31
• Download URL:
  https://stacks.cdc.gov/view/cdc/259975/cdc_259975_DS1.pdf
• File Type:
  [PDF - 1.51 MB]
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:170339a757eb0b57b9327c1f397ea424fc7a00e1f9e3f94e3722201ebff9130d224c32493073ecbb586aba21be07e7ff777aa72f4ff1335e60988a3caa22e0cd