<img height="1" width="1" style="display:none;" alt="" src="https://px.ads.linkedin.com/collect/?pid=1719028&amp;fmt=gif">

How Cognite Data Fusion accelerated condition monitoring for Wintershall Dea

Improved gas turbine monitoring unlocked hundreds of thousands of dollars in savings.

Wintershall Dea used Cognite Data Fusion (CDF) to combine contextualized data with domain expertise and develop machine learning models to monitor the installed gas turbine at the Mittelplate oil field, detecting faulty shutdowns and alerting maintenance engineers to avoid a potential breakdown during restart.

The solution saves Wintershall Dea an estimated $865,000 per incident.

 

 

In Short

Cognite and Wintershall Dea used Cognite Data Fusion, Asset Data Insight, and Model Hosting to operationalize machine learning models at scale, helping maintenance experts monitor the condition of the gas turbine.

Dollars saved
$865,000 saved per incident

Challenge

The installed gas turbine generates electricity to power Wintershall Dea’s installation at the Mittelplate oil field off the coast of Germany. However, the maintenance engineers and electricians responsible for monitoring the turbine still rely on fixed thresholds for alarms and warnings. They have long lacked an easy way to receive early warning about failures and thereby notifying service engineers automatically to perform troubleshooting.

Solution

Cognite worked with Wintershall Dea and the turbine service company to liberate sensor data and events such work orders and collect all the information as a contextualized set in Cognite Data Fusion (CDF). The data is made easily accessible to users in Asset Data Insight, Cognite’s flagship application for smart maintenance.

Cognite and Wintershall Dea’s data scientists then used the contextualized data to build and operationalize machine learning models using CDF’s model hosting service. The outputs from the model are visualized in a Power BI dashboard. The solution provides electricians and maintenance engineers notifications and intuitive dashboards with data that describes the health of the shutdown, which help them better understand the condition of the turbine. From the respective landing pages, the dashboards let users explore sensor trends and warnings for each shutdown, early warnings of deviations from normal shutdowns, and analyses of historical shutdowns.

wdeaturbine

Impact

Wintershall Dea’s rotating equipment maintenance experts estimate that the dashboards will help the company save $865,000 per incident by automatically detecting unhealthy shutdowns, thereby eliminating unplanned downtime and repair costs. With greater access to data and insights, the maintenance and service engineers can move toward a condition-based maintenance strategy, thereby making Wintershall Dea’s operations safer and more reliable.

Request a demo to witness Cognite Data Fusion in action

Book Now

Similar use cases

18 March 2020
How Cognite Data Fusion helps grid operators prevent transformer failures
Read more
18 March 2020
How Cognite Data Fusion speeds up the power grid connection process
Read more
10 March 2020
How Cognite's products helped Aker BP set CO2 reduction goals
Read more