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Challenge
Turbine intelligence was scattered across legacy systems, leaving engineers without a coherent picture of asset health. In offshore environments, where a single turbine contains thousands of interdependent components, conventional software offered little more than surface-level visibility.
The Innovate UK and Eurostars programme turned this project into an R&D initiative. It required methodological depth, scientific discipline and an architecture capable of supporting advanced analytics, anomaly detection and future AI research.
A cloud-native, API-first engineering platform became essential. It needed to consolidate instrumentation data, reveal hidden signals and deliver operational clarity while standing up to academic scrutiny and real-world field demands.
Key Objectives
- Establish a single operational system for global turbine management
- Enable hierarchical navigation from fleet level to individual components
- Consolidate health indicators, alerts and predictive signals in one interface
- Automate engineering task planning using real-time system inputs
- Deliver low-latency performance across remote and distributed networks
- Provide a scalable architecture capable of supporting future R&D outcomes
- Reduce unplanned downtime and elevate operational efficiency
Solution
- A digital engineering platform was designed with research-grade precision and enterprise-level scalability.
- A cloud-native architecture delivered unified visibility across fleets, sites, towers and components. A structured asset hierarchy allowed engineers to move seamlessly from global dashboards to granular component data.
- An API-first integration layer consolidated data from IoT devices, field systems and monitoring equipment. Real-time data pipelines ensured that critical metrics flowed without delay, supporting fast decision cycles.
- The interface translated complex operational signals into clear, actionable insights. Visualisations highlighted risk levels, trend shifts and maintenance priorities with academic clarity and minimal cognitive load.
- Automated scheduling workflows assigned tasks based on system-detected conditions or predicted service windows. Compliance-ready logs captured every action for traceability and regulatory alignment.
- A CI/CD pipeline ensured continuous enhancement, supporting iterative research outcomes from the Innovate UK and Eurostars programme. The platform was engineered to evolve alongside new findings, algorithms and instrumentation introduced during the programme lifecycle.
Results
- A single source of truth established for turbine and asset intelligence
- Complete visibility achieved across global sites, fleets and components
- Faster fault identification enabled significant reductions in downtime
- Automated scheduling improved workforce efficiency and predictability
- Cloud-native architecture delivered frictionless scaling to new fleets and regions
- Data-driven decision making embedded into routine operations
- The platform provided a high-credibility foundation for ongoing R&D and AI innovation
Innovify designs data and engineering platforms that are ready for analytics and AI from day one. Explore AI Labs, or talk to our team about your own platform.
