Space application represents a challenge for the lubrication of tribological components from two perspectives – performance and cleanliness. Due to the vacuum of space, and in particular in the presence of sensitive (e.g. optical) components, an extremely low volatility is required to limit evaporation or outgassing, which can lead to lubricant loss and contamination issues.

The widespread use of COTS in LEO is constrained by their susceptibility to faults and the difficulty in implementing custom fault detection and recovery actions (FDIR) closely to the system in question. Thus, faults may pass undetected until they propagate outside the COTS system and cause a significant impact on the spacecraft. This delay in recovery actions may contribute to lower in-orbit reliability and availability. The challenge is in supporting designers who wish to protect their systems via recurrent methods and tools which are also cost-effective. 

Solar cells for space applications are typically designed to provide highest performance values at End of Life (EOL) conditions, meaning after a typical to be expected degradation due to particle irradiation and under a constant sun spectrum without perturbation by any atmosphere. Typically, these solar cells are used without modification also for Martian missions. However, due to the fact that the spectral conditions on Mars are significantly different from typical space missions, those solar cells are not at all optimised for providing highest performances.

In-Space Assembly and Manufacturing (ISAM) is a revolutionary approach to building and maintaining space infrastructure. By constructing and fabricating components directly in orbit or beyond, ISAM reduces the reliance on Earth-based manufacturing and launch constraints, offering numerous advantages for space exploration, commercial applications, and sustainability. ROBOFAB was proposed as a mission study for redefining how large and complex structures are manufactured and assembled in orbit.

The design process of a typical attitude and orbit control system (AOCS) involves the significant effort of tuning and validation of static controllers or state estimators, calibrated for each mission phase/mode. The transition between these controllers/observers may occur without performance guarantee, as well as provoking settling impacts. The tuning effort and Verification and Validation (VV) process can be improved by Linear Parameter Varying (LPV) techniques.

The project included the design, fabrication, and characterization of key components such as transmission lines, resonators, and third-order filters in GGW technology. These components were manufactured using 3D screen printing and then subjected to rigorous testing to validate their electrical and geometric properties. A key technical challenge was to maintain dimensional tolerances within ±15 µm and surface roughness (Ra) below 3 µm to ensure optimal performance at high frequencies.

While test case definition is test dependent and test performance is human error prone and effort intensive, automated testing proved to be still not reaching a level of abstraction and exhaustiveness to enable significant return on investment.The application of Data Analytics technologies like Machine Learning, Artificial Intelligence or Data Mining to both simulation and test data processing shall provide a level of abstraction and consistency to improve both test automation production and exhaustiveness.