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 utility-scale solar plant operator sought to transition from reactive and preventative maintenance practices toward more cost-effective condition-based approaches. The challenge was identifying performance anomalies and equipment issues early enough to reduce energy losses and maintenance costs, while minimizing false alarms that waste operational resources.
A client sought to expand their capabilities in gas turbine performance monitoring and analysis. They needed both educational resources to help their team understand and apply digital twin technology, as well as refinements to calibration software that would meet rigorous quality standards for deployment.
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.
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.
Power generation operators managing multiple assets often struggle to balance competing priorities: responding quickly to grid demands, maintaining optimal efficiency, and minimizing maintenance impacts across their fleet. Traditional dispatch approaches rely on static models that fail to account for real-time equipment health, leading to suboptimal bidding strategies and reduced profitability.
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