Survival Analysis for Pipeline Longevity and Maintenance Optimization

Aging pipelines pose risks due to environmental degradation, operational stresses, and material fatigue. Traditional risk models lack precision in tailoring maintenance, often overlooking the cumulative impact of recurrent failures within pipeline segments. This study addresses these gaps by proposing a data-driven framework using recurrent event survival analysis, specifically the Prentice, Williams, and Peterson total time and gap time models. The methodology leverages incident data from the Pipeline and Hazardous Materials Safety Administration and network attributes from the US Energy Information Administration. Results show a sharp survival decline in the first operational year, with 35.66% of failures due to equipment defects and operational errors. Subsequent failures accelerate deterioration, highlighting the need for increased inspections following early incidents. Unlike traditional models, which underestimate risk, the proposed method captures the compounded effects of recurrent failures. This study advances pipeline risk assessment through a segment-wise survival model that improves failure prediction and maintenance scheduling.