KUANTIFIKASI KETIDAKPASTIAN PADA ANALISIS POHON KEGAGALAN DENGAN PENDEKATAN FUZZY - Purba, Julwan Hendry; Tjahyani, D.T. Sony (Jurnal Teknologi Reaktor Nuklir Tri Dasa Mega, 2015)
Fault tree analysis has been applied to evaluate nuclear power plant safety systems. To perform this analysis, component reliabilities need to be provided well in advance. Since working environment can affect component reliability, it is necessary to directly collect such data from the safety system being evaluated. However, due to lack of resources, such data may be unattainable. Hence, the use of generic data cannot be avoided. Unfortunately, generic data will add uncertainty to the analysis. Monte Carlo simulation has been performed to evaluate such uncertainty. However, this method is not appropriate when components do not have probability distributions of their lifetime to failures. The aim of this study is to propose a new fault tree analysis method which implements fuzzy concepts for quantifying such uncertainty. In the proposed method, fuzzy probabilities represent basic, intermediate as well as top event probabilities and fuzzy combination rules are used to evaluate the overall uncertainty of the fault tree. The proposed method has been performed to evaluate failure probability of the AP1000 accumulator injection system and generate a probability distribution between 8.87E-12 and 8.87E-8 with the point median value of 8.87E-10. This result confirms that the proposed method is feasible to evaluate system fault tree when uncertainty raised by the lack of reliability data is the main focus of the analysis.