Risk-based inspection and maintenance (RBIM) - Multi-attribute decision-making with aggregative risk analysis

The increasing complexity of oil and gas installations and operations, along with growing public awareness to ensure higher levels of safety, has put great pressure on the designers and operators to find innovative solutions to ensure safe as well as economically viable operation. Risk-based inspection and maintenance helps in finding such solutions and thus in gaining more importance in the industries. A wide range of methodologies currently in use for risk-based inspection includes commercial and in-house software packages (specific to individual plants). The techniques with software produce very different results, raising serious concerns. A recent benchmarking study conducted by the British Health and Safety Laboratory has confirmed the lack of a coherent approach as well as wide variation in the results of the case studies conducted by different agencies. Here, we present a simple and structured risk-based inspection and maintenance methodology that can bridge this gap. The proposed methodology uses fuzzy logic to estimate risk by combining (fuzzy) likelihood of occurrence of and its (fuzzy) consequence. The methodology is based on aggregative risk analysis and multi-attribute decision-making. Application and effectiveness of the proposed methodology is demonstrated using four case studies conducted earlier by different agencies. The results obtained are fairly consistent with little variation and the sensitivity of the proposed method is also discussed in the paper.