Application of Bayesian Network in the EX-Risk-Based Inspection
MetadataShow full item record
- Studentoppgaver (TN-ISØP) 
In the oil and gas industry, many operating expenses assigns to the cost of inspection and maintenance. Therefore, an optimized inspection strategy can reduce the cost of inspection and maintenance when the system's integrity does not change. One of the inspection's main issues is providing the right balance between the benefits of inspection and the inspection cost. It has led to the emerging of a new concept of inspection called risk-based inspection (RBI). This is based on the logical view that most high-risk equipment is concentrated within a small portion of the plant. Therefore, this equipment has priority for inspection, and the extra cost could be decreased with reduced inspection for other equipment with lower risk. Different risk-based inspection approaches have been accepted and developed in the petroleum industry in the past few years. However, there is not any integrated approach for RBI. In this research, to minimize the inspection cost, a new risk-based methodology has been developed by employing the Bayesian Network. Therefore, this study started with the most common risk analysis techniques such as fault tree and event tree and then tried to present a Bayesian network that can deal better with uncertainty. The critical point is that the BN model has met the RBI principle, which required increasing inspection for high-risk equipment to ensure safety level. On the other hand, it makes balance in the cost by reducing the inspection for low-risk equipment.