Human factors always affect maintenance performance, and in
some cases, it’s critical to systems availability and reliability.
Despite such importance, in so many cases, there’s no human
reliability method applied to analyze maintenance tasks in
order to understand better human factors influence in maintenance performance.
There are several human analysis methodologies and regarding human factors,
SLIM (Successes Likelihood Methods), SPAR-H (Standardized Plant Analysis
Risk-Human Reliability Analysis Method) and Bayesian Net take into account such
factors and may be a good approach to minimize human error. In order to propose
a human reliability methodology to analyze maintenance tasks taking into
account human factors, a case study about turbine star up tasks will be
carried out. Therefore, different human reliability methods will be performed
based on specialist opinion. Finally, the human error probability as well as
drawbacks and advantages from different methods will be discussed to get a