Virtualitics

How One Company Uses Virtualitics AI Platform to Save $500,000 Annually in Downtime and Energy Loss

Challenge:
The energy company knew there was a performance problem with some of its wind turbines, but it was unable to pinpoint the root cause. As a result, the company wasted resources trying to assess and resolve the malfunctions.
Approach:
Diagnostics data from multiple sources was added to Virtualitics AI Platform and access to the multidimensional visualization of the schematics was made available to all wind turbine engineers. With the entire team able to explore the maintenance data within a 3D visual they were able to collaborate and pinpoint the source of equipment failure quickly.
Results:

• Virtualitics AI Platform identified the root cause of wind turbine performance issues, saving the company $500,000 annually in downtime and energy loss.
• 3D interactive data exploration helped wind farm engineers visualize and identify the key driver of underperformance.
• AI routines highlighted drivers of energy production and identified ideal operational conditions with respect to auxiliary power.

Transportation company uses Virtualitics to save $6-15M in annual maintenance costs

Challenge
Airplane maintenance is a complex process, especially when it comes to anticipating when a plane may need unscheduled maintenance. Unforeseen maintenance on aircraft can cause huge issues, including downtime, which usually results in lost time and money.
Approach
Our team worked directly with the client to determine all the necessary data sources, predictive needs, and reporting requirements. This ensured that we delivered a product that met their needs while also saving them valuable time and resources. A variety of data sources, including flight logs, historical maintenance reports, and weather data from an external source, were consumed and processed by the Virtualitics AI Platform. Using this information and applying patented AI routines, the Virtualitics AI Platform was able to identify the drivers behind maintenance and downtime and predict where and when maintenance was required.
Results:

• Customized solution yields $6-15M annual savings in estimated maintenance costs.
• Integration into existing workflow helps drive action early and leads to 2-3% decrease in overall machinery downtime.
• Ground team experiences 50% reduction in unscheduled maintenance on monitored systems within the first three months.
• Plus, an integration with the existing part inventory system keeps the necessary replacement parts stocked.