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Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data-Mining Techniques

Author

Listed:
  • Lluís Sanmiquel

    (ICL Chair in Sustainable Mining, Polytechnic University of Catalonia, 08034 Barcelona, Spain)

  • Marc Bascompta

    (ICL Chair in Sustainable Mining, Polytechnic University of Catalonia, 08034 Barcelona, Spain)

  • Josep M. Rossell

    (Department of Mathematics, Polytechnic University of Catalonia, 08034 Barcelona, Spain)

  • Hernán Francisco Anticoi

    (Department of Mining Engineering, Industrial and ICT, Polytechnic University of Catalonia, 08034 Barcelona, Spain)

  • Eduard Guash

    (Department of Mining Engineering, Industrial and ICT, Polytechnic University of Catalonia, 08034 Barcelona, Spain)

Abstract

An analysis of occupational accidents in the mining sector was conducted using the data from the Spanish Ministry of Employment and Social Safety between 2005 and 2015, and data-mining techniques were applied. Data was processed with the software Weka. Two scenarios were chosen from the accidents database: surface and underground mining. The most important variables involved in occupational accidents and their association rules were determined. These rules are composed of several predictor variables that cause accidents, defining its characteristics and context. This study exposes the 20 most important association rules in the sector—either surface or underground mining—based on the statistical confidence levels of each rule as obtained by Weka. The outcomes display the most typical immediate causes, along with the percentage of accidents with a basis in each association rule. The most important immediate cause is body movement with physical effort or overexertion, and the type of accident is physical effort or overexertion. On the other hand, the second most important immediate cause and type of accident are different between the two scenarios. Data-mining techniques were chosen as a useful tool to find out the root cause of the accidents.

Suggested Citation

  • Lluís Sanmiquel & Marc Bascompta & Josep M. Rossell & Hernán Francisco Anticoi & Eduard Guash, 2018. "Analysis of Occupational Accidents in Underground and Surface Mining in Spain Using Data-Mining Techniques," IJERPH, MDPI, vol. 15(3), pages 1-11, March.
    • Handle: RePEc:gam:jijerp:v:15:y:2018:i:3:p:462-:d:135078
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    References listed on IDEAS

    as
    1. Galán, S.F. & Mosleh, A. & Izquierdo, J.M., 2007. "Incorporating organizational factors into probabilistic safety assessment of nuclear power plants through canonical probabilistic models," Reliability Engineering and System Safety, Elsevier, vol. 92(8), pages 1131-1138.
    2. Mallick, S. & Mukherjee, K., 1996. "An empirical study for mines safety management through analysis on potential for accident reduction," Omega, Elsevier, vol. 24(5), pages 539-550, October.
    3. Rivas, T. & Paz, M. & Martín, J.E. & Matías, J.M. & García, J.F. & Taboada, J., 2011. "Explaining and predicting workplace accidents using data-mining techniques," Reliability Engineering and System Safety, Elsevier, vol. 96(7), pages 739-747.
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    Cited by:

    1. Lluís Sanmiquel & Marc Bascompta & Josep M. Rossell & Hernan Anticoi, 2021. "Analysis of Occupational Accidents in the Spanish Mining Sector in the Period 2009–2018," IJERPH, MDPI, vol. 18(24), pages 1-15, December.
    2. Anurag Yedla & Fatemeh Davoudi Kakhki & Ali Jannesari, 2020. "Predictive Modeling for Occupational Safety Outcomes and Days Away from Work Analysis in Mining Operations," IJERPH, MDPI, vol. 17(19), pages 1-17, September.
    3. Rachel Aldred & Susana García-Herrero & Esther Anaya & Sixto Herrera & Miguel Ángel Mariscal, 2019. "Cyclist Injury Severity in Spain: A Bayesian Analysis of Police Road Injury Data Focusing on Involved Vehicles and Route Environment," IJERPH, MDPI, vol. 17(1), pages 1-16, December.
    4. Ahmet Tasdelen & Alper M. Özpinar, 2023. "A Dynamic Risk Analysis Model Based on Workplace Ergonomics and Demographic-Cognitive Characteristics of Workers," Sustainability, MDPI, vol. 15(5), pages 1-11, March.

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