A fuzzy reliability assessment of basic events of fault trees through qualitative data processing

Abstract

Probabilistic approaches are common in the analysis of reliability of complex engineering systems. However, they require quantitative historical failure data for determining reliability characteristics. In many real-world areas, such as e.g., nuclear engineering, quantitative historical failure data are unavailable or become inadequate and only qualitative data such as expert opinions, which are described in linguistic terms, can be collected and then used to assess system reliability. Moreover, experts are more comfortable justifying event failure likelihood using linguistic terms, which capture uncertainties rather than by expressing judgments in a quantitative manner. New techniques are therefore needed that will help construct models of reliability of complex engineering system without being confined to quantitative historical failure data. The objective of this study is to develop a fuzzy reliability algorithm to effectively generate basic event failure probabilities without reliance on quantitative historical failure data through qualitative data processing. The originality of this study comes with an introduction of linguistic values articulated in terms of component failure possibilities in order to qualitatively assess basic event failure possibilities treated as inputs of the proposed model and generate basic event failure probabilities as its outputs. To demonstrate the feasibility and effectiveness of the proposed algorithm, actual basic event failure probabilities collected from nuclear power plant operating experiences are compared with the failure probabilities generated by the algorithm. The results demonstrate that the proposed fuzzy reliability algorithm arises as a suitable alternative for the probabilistic reliability approach when quantitative historical failure data are unavailable.