Mitigating System Failure Risk Across Diverse Pipeline Materials and Decades of Operation
The utility needed a consistent, data-driven method to prioritize maintenance for its entire 740-mile network. This required addressing data gaps and aligning various materials—including cast iron, steel, and PVC—under a unified risk model to effectively manage long-term infrastructure planning and reliability.
Advanced Python-Based Risk Ranking and GIS Integration Tools
Our team addresses the gap between disparate asset records and maintenance action by developing a customized suite of Python tools within ArcGIS Desktop. The solution involves two primary workstreams: refreshing the risk model with the latest asset inventory and adding new, weighted factors identified through collaborative staff workshops. Our team scores pipe segments based on physical characteristics like age and burial depth, proximity factors, and spatial variables such as break density. By integrating hydraulic modeling data, the technology tags each segment with a weighted failure risk score. This approach transforms raw field testing results and condition assessment reports into a comprehensive risk ranking. The solution is designed for repeatability, using an open database design that allows the utility to regularly update the model, ensuring that maintenance focus remains on the highest-risk assets across the entire regional footprint.
Integrated Capital Planning Supporting Proactive Regional Infrastructure Reliability
The updated model significantly reduced system risk by providing a comprehensive ranking for all pipelines. Middlesex Water Company now uses these insights to drive its annual RENEW program, ensuring cost-effective maintenance and reliable service for its customers through a data-justified process.
