Date of Award
12-2009
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Legacy Department
Industrial Engineering
Committee Chair/Advisor
Shappell, Scott A
Committee Member
Gramopadhye , Anand K
Committee Member
Wiegmann , Douglas A
Committee Member
Garrett , Sandra K
Abstract
Historically, mining has been viewed as an inherently high-risk industry. Nevertheless, the introduction of new technology and a heightened concern for safety has yielded marked reductions in accident and injury rates over the last several decades. In an effort to further reduce these rates, the human factors associated with incidents/accidents need to be addressed. A modified version of the Human Factors Classification and Analysis System (HFCAS-MI) was used to analyze lost time accidents and high-potential incidents from across Queensland, Australia and fatal accidents from the United States of America (USA) to identify human factor trends and system deficiencies within mining. An analysis of the data revealed that skill-based errors (referred to as routine disruption errors by industry) were the most common unsafe act and showed no significant differences between accident types. Findings for unsafe acts were consistent across the time period examined. The percentages of cases associated with preconditions were also not significantly different between accident types.
Higher tiers of HFACS-MI were associated with a significantly higher percentage of fatal accidents than non-fatal accidents. These results suggest that there are differences in the underlying causal factors between fatal and non-fatal accidents. By illuminating human causal factors in a systematic fashion, this study has provided mine safety professionals the information necessary to reduce mine accidents/incidents further.
Recommended Citation
Patterson, Jessica, "HUMAN ERROR IN MINING: A MULTIVARIABLE ANALYSIS OF MINING ACCIDENTS/INCIDENTS IN QUEENSLAND, AUSTRALIA AND THE UNITED STATES OF AMERICA USING THE HUMAN FACTORS ANALYSIS AND CLASSIFICATION SYSTEM FRAMEWORK" (2009). All Dissertations. 464.
https://tigerprints.clemson.edu/all_dissertations/464