Reducing the Uncertainty of Marine Accidents Failure Rate in Harsh Environment; Using Bayesian Theory

Reza Gholamnia; Ahmad Bahoo Toroody; Saeed Amirahmadi; Farshad Bahoo Toroody

doi:10.3759/joise.v3i2.3522

Abstract

The interest in arctic activities is strong, but has not led to significant quantifying analysis over the fact of finding rescannable failure rate. To attract investors and promote the development of a marine industry, a clear concept of project risk is paramount; in particular, issues relating to human role in operation are critical. In the public domain, reliability of information is often scarce or inappropriate for such environment. Also, an interdisciplinary study is needed to couple human error probability to operational accidents and failures to work out plausible failure rate. Thus, reliability estimates are fraught with large uncertainties. This paper explores sources and magnitudes of failure rate uncertainty and demonstrates the effect on reliability estimates for lifting operation in cold environment. If generic failure rate data forms the basis of a reliability assessment, reliability estimates are not robust and may significantly over- or underestimate system reliability. The Bayesian statistical framework provides a method to overcome this issue. Generic data can be updated with more specific information that could not be statistically incorporated otherwise. To reduce uncertainty on failure rate, a new methodology is adopted to consider human error probability to find operation accident failure rate. It is proposed that adopting such an approach at an early stage in an iterative process will lead to an improved rate of certainty.