About
Starting Semester: Fall 2026Assigned: No
Location: Atlanta
GE Vernova
Client Profile
GE Vernova’s Gas Power business is a global leader in engineering high-efficiency gas turbine technologies designed to balance the world’s growing demand for electricity with the urgent need for decarbonization. Supporting this mission is a massive global footprint, featuring an installed base of more than 7,000 gas turbines generating approximately 25% of the world’s electricity, all backed by a comprehensive services network that provides life-cycle maintenance, digital diagnostics, and decarbonization upgrades. By combining deep domain expertise with digital controls and carbon-capture integration, GE Vernova provides the essential infrastructure needed to power modern life while accelerating the transition to a lower-carbon energy future.Project Description
GE Vernova’s Monitoring & Diagnostics (M&D) Center serves as the digital pulse of its global fleet, providing a centralized hub for the real-time 24x7 monitoring of more than 950 power plants and over 5000 connected industrial assets. These include 2200+ heavy duty gas turbines, 400+ steam turbines, 2300+ generators, and over 50 heat recovery steam generators.The M&D center is one of the world's largest Network Operations Centers (NOCs) specializing in the energy industry (Power Generation). The facility ingests a massive streaming telemetry load, processing thousands of gigabytes of data daily from sensors embedded throughout its global gas turbine installed base. By bridging high-velocity cloud computing with deep domain expertise, the M&D Center provides 24/7 predictive maintenance guidance that significantly reduces unplanned downtime and optimizes the performance of assets generating a substantial portion of the world's electricity.
The M&D enter is consistently challenged in maintaining high services levels within minimum operating costs. System RAM (Reliability, Availability and Maintainability) are key business KPI’s that need to be proactively managed. The department has invested in a state-of-the art observability platform (Dynatrace) that monitors all aspects of the system performance – data quality, analytics processing, edge devices, network and cloud – at a very granular level and provides a wealth of information that is archived. Today, we do not utilize this information to proactively drive predictive maintenance and reliability across the center.
We would like to develop a Decision Support Tool that leverages system observability data to improve the Reliability of the M&D system. This would (1) Utilize data from Observability Telemetry (Dynatrace) and workforce utilization metrics, (2) Identify reliability areas of concern with supporting failure rate and repair time distributions, (3) Develop customized KPI’s like Health, Condition and Usage Indices, and (4) Develop a reliability modeling and simulation framework that can be used for scenario analysis, system improvement and decision optimization.
In summary this decision support tool will be used to (1) Model the reliability of the M&D center, and (2) Improve reliability through “what-if” scenario analysis and resource optimization.
Skills
People working on this tool should ideally have a strong background in core industrial engineering topics, including• Statistical analysis of data including reliability engineering
• Data Mining and Predictive Modeling skills, including basic supervised and unsupervised learning methods (linear & nonlinear regression, clustering & classification methods)
• Discrete Event Modeling & Simulation
• Some awareness of data center operations – basic understanding of sensors, data acquisition, Edge Devices, Computer Communication Networks and Cloud Computing.
• Strong written communication skills (documentation in MS Office, LaTeX)