Predictive Asset Analytics for a Leading Utility Company
Develop predictive models to understand which factors contribute to pole decay and to predict when inspections should be done to validate the structural soundness of poles. The models should also provide insight into the value of a comprehensive inspection vs. a streamlined inspection and what circumstances warrant each inspection type.
A leading American power and energy company with asset portfolio that includes 25kMW of power generation, 6k miles of electric transmission lines and ~15k miles of natural gas transmission. It also operates the nation’s largest natural gas storage facility. The company faced challenges of frequent pole decay and wanted to streamline inspections and reduce the costs associated with it.
Integrating Predictive Maintenance for electricity distribution pole to understand factors that contribute to pole decay and providing insight to the value of comprehensive inspection v/s a streamlined inspection and circumstances that warrant each inspection type.
- Determining pole failures which could highly impact the electricity supply
- Reduction in overall pole failures and manual inspection resulting in cost savings
- Predictive maintenance enables to look for patterns in pole data, usage and the environment and correlates with any known issues to help predict failures