Off-road truck-related accidents in U.S. mines

Abstract

Introduction Off-road trucks are one of the major sources of equipment-related accidents in the U.S. mining industries. A systematic analysis of all off-road truck-related accidents, injuries, and illnesses, which are reported and published by the Mine Safety and Health Administration (MSHA), is expected to provide practical insights for identifying the accident patterns and trends in the available raw database. Therefore, appropriate safety management measures can be administered and implemented based on these accident patterns/trends. Methods A hybrid clustering-classification methodology using K-means clustering and gene expression programming (GEP) is proposed for the analysis of severe and non-severe off-road truck-related injuries at U.S. mines. Using the GEP sub-model, a small subset of the 36 recorded attributes was found to be correlated to the severity level. Results Given the set of specified attributes, the clustering sub-model was able to cluster the accident records into 5 distinct groups. For instance, the first cluster contained accidents related to minerals processing mills and coal preparation plants (91%). More than two-thirds of the victims in this cluster had less than 5 years of job experience. This cluster was associated with the highest percentage of severe injuries (22 severe accidents, 3.4%). Almost 50% of all accidents in this cluster occurred at stone operations. Similarly, the other four clusters were characterized to highlight important patterns that can be used to determine areas of focus for safety initiatives. Conclusions The identified clusters of accidents may play a vital role in the prevention of severe injuries in mining. Further research into the cluster attributes and identified patterns will be necessary to determine how these factors can be mitigated to reduce the risk of severe injuries. Practical application Analyzing injury data using data mining techniques provides some insight into attributes that are associated with high accuracies for predicting injury severity.

Hazard Identification and Risk Assessment of Occupational Activities in Golgohar Mining Company, Southeast Iran (2021)

“…Losing control of equipment has been reported as the leading cause of machine-related fatalities in surface mining [45]. Based on some studies, occupational groups having the highest percentage of all accidents in mines were maintenance personnel and mechanic repairmen [26,46,47]. Groves et al [48] showed that a significant portion (54%) of accidents in the mining industry was due to material handling, machinery (12%), hand tools (11%), roof falls (10%), and powered haulage (8%).…”

Injuries during the first hour at work in the U.S. mining industry

“…According to this study, the highest proportion of first‐hour injuries were transportation‐related at the mining site. A study by U.S. Bureau of Labor and Statistics in 2011 reported that transportation and contact with heavy equipment‐related injuries were the leading cause of fatalities in the mining industry, which was attributed to the wide use of heavy vehicles such as earthmovers, off‐road trucks, and man‐cars 28,29 . According to previous studies, the most common causes of off‐road truck‐related injury include (i) failure of victim to respect truck area, (ii) failure to maintain adequate berm, (iii) failure of mechanical components, (iv) failure to obey signals, and (v) inadequate training 29‐31 .…”

“…A study by U.S. Bureau of Labor and Statistics in 2011 reported that transportation and contact with heavy equipment‐related injuries were the leading cause of fatalities in the mining industry, which was attributed to the wide use of heavy vehicles such as earthmovers, off‐road trucks, and man‐cars 28,29 . According to previous studies, the most common causes of off‐road truck‐related injury include (i) failure of victim to respect truck area, (ii) failure to maintain adequate berm, (iii) failure of mechanical components, (iv) failure to obey signals, and (v) inadequate training 29‐31 . Dindarloo showed that more than 70% of all off‐road truck‐related accidents happened when the truck operators were either getting on/off the trucks, 29 which corresponds to the disproportionate number of falls we observed in our analysis.…”

“…According to previous studies, the most common causes of off‐road truck‐related injury include (i) failure of victim to respect truck area, (ii) failure to maintain adequate berm, (iii) failure of mechanical components, (iv) failure to obey signals, and (v) inadequate training 29‐31 . Dindarloo showed that more than 70% of all off‐road truck‐related accidents happened when the truck operators were either getting on/off the trucks, 29 which corresponds to the disproportionate number of falls we observed in our analysis. Previous research by Moore et al 32 showed that large trucks, wheel loaders, dozers, and conveyors/belts, etc.…”

Simulation-Based Assessment of Multilane Separate Freeways at Toll Station Area: A Case Study from Huludao Toll Station on Shenshan Freeway

“…Moreover, existing fee policies related to truck lane restrictions were analyzed and characterized the state of the practice in permit fees for trucks on public freeways, evaluating these practices at the economic level [19]. Other aspects of related research include emissions, safety, fuel consumption, pavement performance, and characteristics of truck drivers [20][21][22][23][24]. Readers can refer to the above-mentioned literature for more details.…”