Resources

How specifically can an organization implement and use analytics to make an impact? In the video below, Alec Miller and Dr. George Garforth share their experience with implementing self-service analytics to provide: 1) Actionable Insights. 2) Improved Communications. 3) An Ongoing Feedback Loop. Follow up with our Self-Service Guide to begin implementing today. 

There are lots of buzzwords that are used to talk about analytics and digital tools, such as Digital Twin, AI, and Machine Learning.  These are critical technologies that are affecting every industry, but how practically can these be used to improve the operations of wind turbines?   Download our guide, "Beyond the Hype: Self-Service Analytics to Really Get Things Done," and start improving your.

Explore the infographic below to learn why RWE partnered with NarrativeWave to automate corrective actions , saving time and money on turbine fixes at every level.

Imagine if instead of monitoring and routinely reacting to alerts, you could create valuable insights, predict failures, and automate corrective actions.   We make it easy for you to combine the power of advanced analytics with your engineering knowledge to go beyond monitoring - improving asset performance and engineering productivity.

In this video, NarrativeWave and Enel share how they partnered to help Enel transition from reactive to proactive operations, and what it took to really get there. Enel Green Power successfully made the transition from having unplanned failures and excessive downtime, to using predictive analytics that significantly reduced downtime and supply chain costs, while improving overall system.

RWE shares how they transitioned from using the original equipment manufacturer’s (OEM) maintenance services to self-performing the maintenance activities.  As a result, RWE has reduced the time it takes to identify corrective actions, reducing the number of turbine visits, and improving internal processes. Learn more by filling out the form below.

   In this case study, Enel Green Power highlights how they can now predict a critical asset failure 54 days in advance. As a result, Enel can now predict the maintenance needs of their plants and streamline the detection-to-repair process, significantly reducing operational downtime, boosting efficiency and cutting O&M costs.   Learn more by filling out the form below.

  Oil & gas performance operators lack critical insights into how assets are operating, from knowledge of efficiency to advanced notice of failures.    They are surprised by sudden asset failures, causing significant downtime. Living in the reactive, they rarely have the chance to optimize pump operations. Scroll below to dive into a NarrativeWave software use case, featuring Oil & Gas. 

  Enel successfully made the transition from having unplanned failures and excessive downtime, to using predictive analytics that significantly reduced downtime and supply chain costs.  Using NarrativeWave’s solution and transparent predictive analytics, Enel now has an average 54 days in advance notice of critical asset failure. Scroll below to dive into a NarrativeWave software high-level.