A BOW-TIE BASED RISK FRAMEWORK INTEGRATED WITH A BAYESIAN BELIEF NETWORK APPLIED TO THE PROBABILISTIC RISK ANALYSIS

Abstract

The use of probabilistic risk analysis in the jet engines manufacturing process is essential to prevent failure. It has been observed in the literature about risk management that the standard risk assessment is normally inadequate to address the risks in this process. To remedy this problem, the methodology presented in this paper covers the construction of a probabilistic risk analysis model, based on Bayesian Belief Network coupled to a bow-tie diagram. It considers the effects of human, software and calibration reliability to identify critical risk factors in this process. The application of this methodology to a particular jet engine manufacturing process is presented to demonstrate the viability of the proposed approach.