CASE STUDIES » POWER PRODUCTION FORECASTING

Case Studies

Explore how Turbine Logic helps companies like yours optimize the performance of your assets through advanced analytics, diagnostics, and engineering expertise.

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Other Studies

Turbine Monitoring and Technical Support Services

A client in the power generation industry sought specialized expertise to enhance their turbine monitoring capabilities and ensure reliable operational support for their rotating equipment assets. The organization needed access to advanced diagnostic tools and experienced engineers who could provide ongoing technical guidance for complex turbine systems.

Software Review and Technical Support for Power Industry Analytics

A client in the power generation sector needed specialized support for an internal software tool used to analyze and benchmark operational data. Over time, the tool had grown in complexity and adoption, creating a need for expert review of its underlying architecture and hands-on assistance with applied use cases.

Firing Temperature Assessment for Heavy-Duty Gas Turbines

A power generation client needed to understand whether maintenance activities had impacted the firing temperature of their heavy-duty gas turbine fleet. Changes in firing temperature can significantly affect both performance and component life, making accurate assessment critical for operational decision-making and long-term asset management.

Gas Turbine Digital Twin Training and Software Development

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.

Cycle Model Development for Gas Turbine Fault Diagnostics

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.

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