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Sirvi Autor "Lezdkalne, J." järgi

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  • Pisipilt
    Kirje
    Integrating human factors into occupational accident investigation: a literature review of methodologies and their applications
    (Estonian University of Life Sciences, 2025) Lezdkalne, J.
    Introduction: Accident investigation is essential in safety management, aiming to identify causes and prevent recurrence. Despite various methodologies, gaps remain in information collection and human factors integration. Since data collection is the foundation of investigations, deficiencies can compromise conclusions. This study reviews literature on human factors, focusing on their integration into investigation of occupational accidents. The review explores the nature of human factors and investigation methods that address cognitive, psychological, and organisational dimensions. The study also proposes an integrated investigation flow that combines these methodologies to enhance the accuracy and effectiveness of accident investigations. Methods: A literature review was conducted using academic databases. Keywords included ‘accident investigation’, ‘human factors’, and ‘occupational safety’. Inclusion criteria focused on articles, books, and reports from 1990 to 2025, covering topics of interest and safety-critical industries. Relevant literature was screened and analysed based on its contributions to the research topic. Key investigation methodologies were analysed for their strengths and limitations. Results: The study revealed a multitude of methodologies available, each with its own set of strengths and limitations. HFACS, HEART and FMEA methods were analysed for their potential to systematically integrate human factor. While these methodologies demonstrate significant promise, their implementation remains inconsistent due to challenges related to training, organisational culture, and resource allocation. Conclusions: This review emphasizes the importance of integrating human factors into accident investigation methodologies to enhance workplace safety. While traditional methods remain valuable for their accessibility, systemic approaches are essential for addressing complex sociotechnical systems. Future efforts should prioritize investigator training and promotion of positive organisational culture to mitigate human factor challenges and improve investigative outcomes.
  • Pisipilt
    Kirje
    Potentially fatal incidents: identification, classification and human factor analysis
    (Estonian University of Life Sciences, 2026) Lezdkalne, J.
    Potentially fatal incidents (PFIs) are increasingly used as leading indicators in high-risk industries, yet their definitions, classification criteria, and investigative depth vary widely across organisations, limiting. their preventive value and comparability. Human factors (HF) play a critical role in determining whether incidents escalate into PFIs and must be considered together with technical and organisational barrier performance. This research aims to examine the role of human and organisational factors in PFI identification, analyse misclassification patterns, and propose a human-factors-based model to improve PFI classification consistency and learning value. A retrospective document analysis was conducted using incident reports from a heavy-industry organisation covering the period from 2020 to 2024. The dataset was systematically reviewed and PFI classifications were re-evaluated using a structured framework integrating hazardous energy and exposure assessment, barrier performance evaluation based on Bow-Tie logic, and human and organisational factor coding using an HFACS-based structure. Analysis revealed inconsistency in PFI classification, including overclassification and under-classification linked to limited recognition of human and organisational factors. Number of incidents were labelled as PFIs despite lacking credible fatal energy exposure, while other events with systemic and human-factor contributors associated with fatal risk were not recognised as PFIs. The HF-PFI Model demonstrated improved classification reliability by integrating energy exposure, barrier status, human factor categories, and systemic indicators. Integrating human-factors analysis into PFI identification can strengthen serious injury and fatality prevention in high-risk industrial environments.