THE IMPACT OF SAFETY PERFORMANCE MEASURES AND STRUCTURAL FACTORS ON UNDERGROUND COAL MINE PRODUCTIVITY 03-07

Open Access
Author:
Eslambolchi, Safa
Graduate Program:
Energy and Mineral Engineering
Degree:
Master of Science
Document Type:
Master Thesis
Date of Defense:
July 21, 2010
Committee Members:
  • Dr R Larry Grayson, Thesis Advisor
  • R Larry Grayson, Thesis Advisor
Keywords:
  • underground coal mines
  • regression analysis
  • safety
  • productivity
  • mine size transition
Abstract:
Safety in the underground coal mine industry has always been a concern. The Mine Safety and Health Administration (MSHA) enforces safety rules and regulations by periodically inspecting the mines and recording the violation(s) and issuing citation(s) for them. Violations can impact the production of a mine depending on their severity. Some violations can result in temporary mine closure which significantly impacts the production, or permanent mine closure, in which case the production stops forever. After three disasters in 2006, the “MINER Act of 2006” was passed which strengthened the “Federal Mine Safety and Health Act of 1977” by mandating new laws and safety regulations. The MINER Act increased the chance of getting citations and consequently a significant increase in the penalty amounts in 2006 compared to the previous years. These issues could impact the production of the mines until. In this thesis, MSHA databases were used to study the mine-size transitions and the productivity. In the mine-size transition study, the MSHA address/employment database was used to observe the mine-size transitions of 454 underground coal mines in the 5-year period of 2003-2007. This study showed that Very Large and Large mines were the most faithful to their size category. In the second study, MSHA address/employment, accident/injury, and inspection databases were used to study the impact of safety measures and structural factors on the productivity of underground coal mines in the period of 2003-2007. For this study, mines were categorized in three categories of Very Large/Large, Medium, and Small/Very Small. Using Forward and Backward Stepwise regression methods a robust multi-linear regression model was generated for each mine-size category to find the significant factors impacting the productivity of the mines in each category.