Mining Project: Identification of Key Factors Affecting Machine-related Fatalities and Injuries in MNM Mining Sectors

Principal Investigator
Start Date 10/1/2018
Objective

To identify key factors influencing high incident rates around machinery and powered haulage in the mining industry in order to then identify research gaps to focus on for reducing mine worker machinery-related fatalities and injuries.

Research Summary

Machine-related accidents are currently one of the major causes of fatalities and injuries across the metal/nonmetal (MNM) and stone, sand, and gravel (SSG) mining sectors. The SSG sector, which has a relatively large number of small mine operators, has particularly high non-fatal incident rates. Statistically, machinery and powered haulage lead to a significant number of fatal injuries in mining. Researchers have pointed out that human-machine interactions lead to most of the fatalities and injuries [Groves et al. 2007; Kecojevic et al. 2007; Ruff et al. 2011; Zhang et al. 2014]. Mine Safety and Health Administration (MSHA) accident, illness, and injury data collected during 2010-2017 also show that 48% of all the MNM and SSG mining sectors fatalities were attributed to machinery and powered haulage, with 17% leading to non-fatal injuries.

Most past studies on machine-related accidents have relied heavily on MSHA data; however, there is a need to further interpret MSHA fatality reports for the period 2010-2017 and conduct an in-depth analysis to identify key contributing factors. The NIOSH Mining Program has the expertise and resources in engineering and statistical analysis for conducting such research.

As a one-year pilot project, this research will guide the development of the MNM and SSG mining machine safety research portfolio for the Mining Program. The sole research aim of this project is to conduct a root cause analysis of machine-related fatalities and injuries in the MNM and SSG mining sectors in order to determine focus areas and gaps for future research. Text analytics techniques via MATLAB Text Analytics Toolbox will be utilized for identifying keywords. Also, MSHA data will be studied for statistical correlations. NIOSH researchers will also visit mine sites with high and low accident and fatality incident rates based on the preliminary investigation of the MSHA data in order to learn about and assess their safety programs and to collect feedback on sources of accidents and near misses. All accidents involving machinery, powered haulage, and hoisting as classified by MSHA will be considered in this research.

References

Groves WA, Kecojevic VJ, Komljenovic D [2007]. Analysis of fatalities and injuries involving mining equipment. J Safety Res 38(4):461-470.

Kecojevic V, Komljenovic D, Groves W, Radomsky M [2007]. An analysis of equipment-related fatal accidents in U.S. mining operations: 1995-2005. Safety Sci 45(8):864-874.

Ruff T, Coleman P, Martini L [2011]. Machine-related injuries in the U.S. mining industry and priorities for safety research. Inter J Injury Control and Safety Prom 18(1):11-20.

Zhang M, Kecojevic V, Komljenovic D [2014]. Investigation of haul truck-related fatal accidents in surface mining using fault tree analysis. Safety Sci 65:106-117.


Page last reviewed: 2/21/2019 Page last updated: 2/10/2019