Speaker
Description
Fusion energy is no longer a distant dream—it’s a global industrial race. With around 80 private companies and €13 billion in cumulative funding since 2020, the sector is now targeting near-term power plant deployment. Yet, as the sector races toward commercialization, a critical blind spot persists: the lack of mature Reliability, Availability, Maintainability, and Inspectability (RAMI) frameworks to underpin lifetime performance, economic viability, and scalability.
Current fusion designs often prioritize plasma and plant performance over operational resilience, leaving unanswered questions about plant availability, maintenance feasibility, and inspectability challenges in severe environments. Without validated RAMI methodologies, projections for Levelized Cost of Energy (LCOE) remain highly speculative, threatening investor confidence and the feasibility of deploying thousands of plants. The absence of standardized RAMI approaches risks overly optimistic projections—from downtime modelling to component degradation and maintenance strategies—that could prove dangerously overconfident.
However, this gap presents a transformative opportunity. As fusion transitions from lab to grid, the demand for data-driven RAMI tools, predictive maintenance models, and AI-enabled diagnostics will surge. Organizations that develop credible, scalable RAMI frameworks—capable of integrating real-time operational data, material science advancements, and probabilistic risk assessments—will not only de-risk fusion projects but also define the standards for a new energy paradigm. To achieve this, lessons from other high-tech industries—such as accelerators—must be leveraged.
RAMI is no longer a secondary consideration, it is the cornerstone of fusion’s industrial future, and the time to act is now.