In this paper, a data-driven model is applied to derive optimum maintenance strategy for a petroleum pipeline. The model incorporates structured expert judgment (classical model) to calculate the frequency of failure, considering various failure mechanisms. Optimization models are applied to derive optimum maintenance intervals for petroleum pipelines on the basis of the frequency of failure estimated. Two separate maintenance-optimization models are proposed. The first is a use-based optimization model that minimizes the expected total cost from a petroleum pipeline. The second is a benefit/cost (B/C) -ratio model that seeks to maximize the benefit derived from the pipeline, while minimizing operation and failure costs. The B/C-ratio model is less data intensive, and it has been used to optimize failure data obtained in the classical model. In this approach, the maintenance optimization is a further attempt at reducing the influence of subjectivity in maintenance decisions.
According to Gabbar and Kishawy (2011), integrity of pipelines is the cornerstone of many engineering systems, which explains why pipeline maintenance is taken very seriously by major service companies, especially those involved in the transmission of oil and gas. The huge impact of pipeline failure on operational costs has necessitated the development of more-effective risk-management strategies to help mitigate potential risks. Ideally, most pipeline operators ensure that during the design stage, safety provisions are created to comply with a theoretical minimum failure frequency for the pipeline.
Quantitative risk assessment (QRA) has been a valuable tool to operators in minimizing risk and complying with the minimum safety requirements for engineering structures. QRA of pipeline networks is complex and can sometimes be laborious because of the differences in the system networks. According to Li (2007), one approach to simplify the QRA process is the use of the hierarchical approach. Hierarchical approaches, such as fault-tree analysis, event-tree analysis, and failure-mode event analysis, have found applications in risk assessment for complex structures, as explained in Dhillon and Singh (1981). However, such methodologies are data intensive. The rupture of pipelines occurs rarely in most countries, and as such, the data of failures are often insufficient to carry out a thorough hierarchical approach. Also, when failure data are gathered, the classifications may not cover all the known failure mechanisms and attributes.
A systematic approach to integrity maintenance of pipelines has been proposed in this paper using the classical model proposed by Cooke (1991). The model is a structured expert-judgment-based approach and is able to provide rational probability assessments. According to Cooke and Goossens (2008), the classical model has been applied successfully to more than 45 expert elicitation case studies, covering both academic and industrial areas. One of the benefits of the approach is that the level of subjectivity in expert judgment is reduced reasonably. This is because of the performance-based calibration of the experts used in the model. In other words, the inputs from the experts are used on the basis of the consistency of the experts during the elicitation process.