Prioritisation of factors contributing to human error for airworthiness management strategy with ANP

YAZGAN E., KÜÇÜK YILMAZ A.

AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY, cilt.91, sa.1, ss.78-93, 2019 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 91 Sayı: 1
  • Basım Tarihi: 2019
  • Doi Numarası: 10.1108/aeat-11-2017-0245
  • Dergi Adı: AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Sayfa Sayıları: ss.78-93
  • Anahtar Kelimeler: Human error, Analytic network process, Multi-criteria decision analysis, Aircraft maintenance technician, Aircraft maintenance organization, PERFORMANCE SHAPING FACTORS, ANALYTIC NETWORK PROCESS, AVIATION MAINTENANCE, SELECTION, SUPPLIER
  • Anadolu Üniversitesi Adresli: Evet

Özet

Purpose Airline business management is set on airworthy strategy. Airline sustainability depends upon corporate-based airworthy strategy as airworthiness is the base to any airline business management and strategy. An airline can ensize its corporate sustainability if it has airworthiness strategy and risk management. The main condition to survive in the airline business is to maintain airworthiness with the fleet, maintenance and corporate-risk management. Aircraft maintenance technician (AMT) has a dual role in aircraft maintenance system as the source of failure in maintenance process via his volatility and unmanageable qualifications and secondly source of manager of maintain airworthiness of the aircrafts in airline. Situational awareness of managers about both limitations and qualifications of human factors is vital determinant to the decision-making process in aviation. Although continuously improving in related literature, one of the biggest weaknesses of the current methods of AMT error or performance is that the ability to model the reciprocal effects of the factors affecting the fault is limited. For this reason, this study aims to develop an analytic network process (ANP) model that takes into account the effects of mutual dependences among factors.