With thousands of turbines distributed across North America, EDF Renewables sought a tool to better monitor and measure the efficiency of the Return to Service of turbines down over 72 hours. In addition to helping identify improvement opportunities, the tool is providing transparency for stakeholders, reducing the manual effort required by site managers, improving issue escalation, and quantifying the cost of delays, all through an intuitive web application accessible across the enterprise. Utilizing Asset Analytics, Event Frames, and an AF SDK-based service, this session will cover how we’ve created a sophisticated system that
-Tracks long-term downtime events and provides a method for updating their status
-Automates, and notifies stakeholders of, event open and close
-Reports KPIs such as average/median downtime, lost revenue, and classifications
Implemented over the past 10 months, the downtime tracking tool has become the cornerstone of EDFR’s performance optimization initiative.
Kelsey Bobeck is an Analytics and Intelligence Engineer with EDF Renewables focused on improving user experience, modernizing EDFR’s PI infrastructure security and architecture, and expanding automation to drive operational awareness. A recent transplant to San Diego, CA, Kelsey enjoys exploring her new home and taking advantage of hiking in the surrounding area.