Case Studies
Explore how Turbine Logic helps companies like yours optimize the performance of your assets through advanced analytics, diagnostics, and engineering expertise.
Other Studies
A client needed to expand their gas turbine monitoring and diagnostic capabilities to cover additional equipment types within their fleet. Existing digital twin models were limited to certain turbine configurations, creating gaps in their ability to perform comprehensive performance analysis across all assets.
A client in the power generation industry sought to enhance their operational capabilities through advanced digital modeling of gas turbine assets. The goal was to create a sophisticated monitoring solution that could provide deeper insights into turbine performance and support data-driven decision making.
A client in the power generation sector sought to explore how emerging digital twin technologies could be applied to improve asset reliability and operational intelligence. While the concept of digital twins had gained significant traction across industries, there was uncertainty about which specific applications would deliver meaningful value for their particular equipment and operational challenges.
A client sought to improve their ability to detect and diagnose equipment faults in their gas turbine fleet before they led to costly unplanned outages. Traditional monitoring approaches were reactive, often identifying problems only after performance had already degraded significantly.
Gas turbine monitoring and diagnostics centers frequently encounter false alarms that consume valuable time and resources. Many of these false alarms stem from issues within the instrumentation chain: sensors that have drifted, failed, or produced corrupted data during transmission or storage.
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