Availability of Conceptual Machines - How and Why? A Case Study of the Future Circular Electron-Positron Collider

In large-scale, high-criticality technical systems, availability is a key performance driver and can offer significant advantages when analysed at an early stage. However, assessing availability during the conceptual design phase remains a major challenge, as traditional methods rely on mature system architectures and detailed component data—resources typically unavailable at early stages. This limitation hinders strategic design decisions and increases the risk of costly late-stage redesigns.
This thesis presents a generalised framework for availability forecasting in conceptual systems, where design details are incomplete. A Monte Carlo-based simulation environment is developed that estimates key performance indicators and decomposes them into subsystem contributions. This supports performance optimisation and helps to translate top-level goals into reliability requirements.
The methodology is demonstrated using the Future Circular Collider (FCC-ee) as a case study, illustrating its benefits and value in a real-world context. Beyond this application, the framework is designed to be domain independent and adaptable to other complex systems, offering structured support for early-stage design and reliability-focused planning.