Human error risk assessment for shipping maintenance procedures in harsh environments

• Main Authors: Abaei, MM, Arzaghi, E, Abbassi, R, Garaniya, V
• Format: Conference Object
• Language: English
• Published: Memorial University Newfoundland 2017
• Subjects: risk assessment; human error; shipping maintenance; harsh environments; FRAM; Antarctic; Arctic; Antarc*
• Online Access: https://eprints.utas.edu.au/25765/; https://eprints.utas.edu.au/25765/1/122350%20-%20Human%20error%20risk%20assessment%20for%20shipping%20maintenance%20procedures%20in%20harsh%20environments.pdf; https://www.mun.ca/engineering/crise/workshops/crise3/

Human factors play a significant role in increasing the operational safety of maritime transport and offshore facilities. A significant number of human errors occur during the maintenance phase. However, the qualification of human error interpretation before undertaking any quantification in the maintenance procedure should be given more attention. It is necessary to find a reasonable qualitative non-linear based method with good interpretation of WHY and HOW accidents occur. This provides good insight, sources of risk and the possibilities for minimizing the potential risk. As maritime operations move into Arctic and Antarctic environments, this will become even more crucial. Decision makers must therefore be able to recognize how cold weather affects human performance and work out how availability, survivability or maintenance of a system goes wrong. This will help assessors to review the details of the process and ask relevant questions rather than blindly finding answers. This paper presents a new reciprocal interaction of qualitative risk-based methodology for human error estimation by applying “Functional Resonance Analysis Method” (FRAM). This methodology has the potential to be considered the first step of any future quantitative assessment for human error estimations. The present study is an imperative milestone for coupling between nonlinear qualitative and quantitative based methods in risk assessment to systematically identify human errors. The developed methodology has been applied to a case study for the maintenance of a component in a ship sailing in a harsh environment.