| dc.description.abstract | Despite substantial improvements in
technological reliability and system safety, human error
remains the prominent cause of accidents in the aviation
industry. There is a pressing need for enhanced
methodologies to model the factors leading to human error
incidents. This study employed the errors caused by
employees to analyze and model the correlation between
causal factors contributing to aviation mishaps. A
comparative analysis of documented and non-documented
accident/ incident data focused on general aviation
maintenance to systematically assess the impact of human
errors and identify potential causal factors. The
methodology was built upon prior research in
understanding causal relationships, utilizing Structural
Equation Modeling (SEM) to simulate the complex
relationships between accident/incident causation and the
triggering factors behind them. Additionally, a framework
was established using the Human Factors Analysis and
Classification System to pinpoint key areas that the
stakeholders of aviation safety should focus on to reduce
similar human errors in the future. The findings
demonstrate an insightful approach to assessing the
quantitative correlations between causative elements,
offering insights not easily obtainable from occurrence rate
analysis alone. Additionally, the findings elucidate
theoretical and managerial implications to minimize human
errors, thus enhancing the overall safety and quality of
aircraft maintenance. The paper discusses the practicality
of the framework, and its potential applicability to the other
domains of aviation and suggests avenues for future
research. | en_US |
