Human factors in aviation maintenance: task design and safety implications
Eksploatacja i Niezawodnosc, cilt.29, sa.1, 2027 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 29 Sayı: 1
- Basım Tarihi: 2027
- Doi Numarası: 10.17531/ein/225076
- Dergi Adı: Eksploatacja i Niezawodnosc
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, Directory of Open Access Journals
- Anahtar Kelimeler: aviation maintenance, cognitive workload, human factors engineering, predictive modeling, support vector machine
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Yıldız Teknik Üniversitesi Adresli: Evet
Özet
Aviation maintenance remains a safety-critical domain where human-factor-related errors persist despite technological advancements and regulatory oversight. Traditional human factors approaches are often retrospective, limiting predictive insight when task design, cognitive workload, fatigue, and procedural ambiguity exceed human capacity. This study addresses that gap by developing and validating a Human Performance Integration (HPI) Model, a predictive, engineering-oriented framework that quantitatively links maintenance task design characteristics with cognitive constraints and error probability. A mixed-methods research design integrates qualitative insights from semi-structured interviews with licensed maintenance technicians (n = 21) and quantitative analysis of 47 incident reports from a regional airline. Qualitative findings inform the identification of latent performance drivers, which are operationalized into measurable variables and structured using Principal Component Analysis (PCA). A Support Vector Machine (SVM) classifier is then applied to model non-linear interactions among cognitive workload, fatigue accumulation, task complexity, and documentation clarity. From an engineering perspective, the HPI model functions as a proactive task evaluation and design-support tool moving beyond post- hoc safety analysis. It enables designers and maintenance engineers to assess how alternative task structures, documentation strategies, and workload allocations influence human performance margins during the planning stage. By embedding human performance constraints directly into task design evaluation, this research advances engineering design knowledge for safety- critical socio-technical systems and contributes a predictive lens to human factors in aviation maintenance.