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Mineworkers’ Perceptions of Mobile Proximity Detection Systems

  • Jennica L. BellancaEmail author
  • LaTasha R. Swanson
  • Justin Helton
  • Michael McNinch
Article
  • 9 Downloads

Abstract

Accident data indicates that mobile haulage poses a significant pinning, crushing, and striking risk. Proximity detection systems (PDSs) have the potential to protect mineworkers from these risks. However, unintended consequences of mobile PDSs can undermine the safety benefit they provide. Soliciting iterative user input can improve the design process. Users help provide a critical understanding of how mobile PDSs may hinder normal operation and endanger mineworkers. Researchers explored users’ perspectives by conducting interviews with mineworkers from seven mines that have installed mobile PDSs on some of their haulage equipment. Mineworkers reported that mobile PDSs affect loading, tramming, section setup, maintenance, and general work on the section. Mineworkers discussed the operational effects and increased burden, exposure, and risk. Mineworkers also suggested that improved task compatibility, training, logistics, and PDS performance might help address some of these identified issues. This paper also gives additional insights into mobile PDS design and implementation.

Keywords

Proximity detection Mining Usability Task compatibility Unintended consequences 

Notes

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Disclaimer

The findings and conclusions in this paper are those of the authors and do not necessarily represent the official position of the National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention. Mention of company names or products does not constitute endorsement by NIOSH.

References

  1. 1.
    Mine Safety and Health Administration (2015) Preliminary regulatory economic analysis for proximity detection systems for mobile machines in underground mines. Proposed Rule. Office of Standards, Regulations, and VariancesGoogle Scholar
  2. 2.
    Mine Safety and Health Administration (2015) Proximity detection systems for continuous mining machines in underground coal mines. 30 CFR 75.1732, vol 1219-AB65. Federal RegisterGoogle Scholar
  3. 3.
    Mine Safety and Health Administration (2015) Proximity detection systems for mobile machines in underground mines. 30 CFR 75.1733, vol 1219-AB78. Federal RegisterGoogle Scholar
  4. 4.
    Mine Safety and Health Administration (2015) Fact sheet: proposed rule on proximity detection systems for mobile machines in underground minesGoogle Scholar
  5. 5.
    Ruff TM (2007) Recommendations for evaluating and implementing proximity warning systems on surface mining equipment. National Institute for Occupational Safety and Health, Spokane, WAGoogle Scholar
  6. 6.
    Bissert PT, Carr JL, DuCarme JP (2016) Proximity detection zones: designs to prevent fatalities around continuous mining machines. Prof Saf 61(6):72–77Google Scholar
  7. 7.
    Haas EJ, Rost KA Integrating technology: Learning from mine worker perceptions of proximity detection systems. In: Proceedings of the 144th Annual Society for Mining, Metallurgy, & Exploration Conference, Boulder, CO, 2015. pp 15–18Google Scholar
  8. 8.
    Kingsley Westerman CY (2010) Behavioral considerations for proximity warning implementation. Paper presented at the Proximity Warning Systems for Mining Equipment, Charleston, WVGoogle Scholar
  9. 9.
    Lynas D, Horberry T (2011) Human factor issues with automated mining equipment. The Ergonomics Open Journal 4(1)Google Scholar
  10. 10.
    Sarter NB, Woods DD, Billings CE (1997) Automation surprises. In: Handbook of human factors and ergonomics. 2 edn., pp 1926–1943Google Scholar
  11. 11.
    Horberry T, Burgess-Limerick R, Steiner LJ Human-centered design for mining equipment and new technology. In: Proceedings 19th Triennial Congress of the IEA, Melbourne, 2015Google Scholar
  12. 12.
    Horberry T, Burgess-Limerick R, Steiner LJ (2010) Human factors for the design, operation, and maintenance of mining equipment. CRC PressGoogle Scholar
  13. 13.
    Peters RH, Vaught C, Hall EE, Volkwein JC (2007) Miners’ views about personal dust monitors. J Int Soc Respir Prot 24(3/4):74Google Scholar
  14. 14.
    Watson G (1971) Resistance to change. Am Behav Sci 14(5):745–776CrossRefGoogle Scholar
  15. 15.
    De Kock A, Oberholzer JW (1997) The development and application of electronic technology to increase health, safety, and productivity in the South African coal mining industry. IEEE Trans Ind Appl 33(1):100–105CrossRefGoogle Scholar
  16. 16.
    Steiner L, Cornelius K, Turin F (1999) Predicting system interactions in the design process. Am J Ind Med 36(S1):58–60CrossRefGoogle Scholar
  17. 17.
    Little C (1997) The intelligent vehicle initiative: advancing “human-centered” smart vehicles. Public Roads Mag 61(2):18–25Google Scholar
  18. 18.
    Schaudt WA, Bowman DS, Baker S, Hanowski RJ, Flanigan C (2013) Field evaluation of an enhanced rear signaling system for heavy trucks. IET Intell Transp Syst 7(3):345–350CrossRefGoogle Scholar
  19. 19.
    Breuer J, von Hugo C, Mücke S, Tattersall S (2015) User-oriented evaluation of driver assistance systems. In: Handbook of Driver Assistance Systems. pp 1–15Google Scholar
  20. 20.
    Tijerina L (1999) Operational and behavioral issues in the comprehensive evaluation of lane change crash avoidance systems. Transp Hum Factors 1(2):159–175CrossRefGoogle Scholar
  21. 21.
    Xiong H, Boyle LN (2012) Drivers’ adaptation to adaptive cruise control: examination of automatic and manual braking. IEEE Trans Intell Transp Syst 13(3):1468–1473CrossRefGoogle Scholar
  22. 22.
    Dogan E, Rahal M-C, Deborne R, Delhomme P, Kemeny A, Perrin J (2017) Transition of control in a partially automated vehicle: effects of anticipation and non-driving-related task involvement. Transport Res F: Traffic Psychol Behav 46:205–215CrossRefGoogle Scholar
  23. 23.
    Tullis T, Albert B (2008) Measuring the user experience: collecting, analyzing, and presenting usability metrics. Morgan Kaufmann PublishersGoogle Scholar
  24. 24.
    Office of Management and Budget (1995) Controlling Paperwork Burdens on the Public; Regulatory Changes Reflecting Recodification of the Paperwork Reduction Act. 5 CFR 1320, vol 60–167. Federal RegisterGoogle Scholar
  25. 25.
    Cho JY, Lee E-H (2014) Reducing confusion about grounded theory and qualitative content analysis: similarities and differences. Qual Rep 19(32):1–20Google Scholar
  26. 26.
    De Kock A, Bennett A (2018) Collision awareness - capability of underground mine vehicle proximity detection systems. Australian Coal Association Research ProgramGoogle Scholar

Copyright information

© This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection  2019

Authors and Affiliations

  1. 1.Pittsburgh Mining Research DivisionNational Institute for Occupational Safety and Health, Centers for Disease Control and PreventionPittsburghUSA
  2. 2.Spokane Mining Research DivisionNational Institute for Occupational Safety and Health, Centers for Disease Control and PreventionSpokaneUSA

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