The efficient management of common consortium activities and the effective coordination of the project were insured during period 2 (WP6).
WP1 has reached all its main objectives for the RP2 reporting period. However, some risks and deviations incurred, and they are detailed in the appropriate chapter together with the mitigation measures applied. The time to perform MDO to find the optimal geometry and then print it, post process it and perform the tests might be off the actual deadline of the project. Thus, the real size module might be tested with the optimal geometry found by design of experiment instead of coming from the MDO. This deviations and risks brought to the need of having an amendment where project extension and budget shifts have been requested and approved.
WP2 has reached all its main objectives for the RP2 reporting period as well as within the broader project scope. Despite facing challenges, such as unforeseen technical complexities or resource constraints, strategic problem-solving ensured the fulfilment of goals. However, it's worth mentioning that submitting the deliverables planned for the 2nd Reporting Period posed a notable challenge. Despite encountering hurdles, WP2 ultimately led to the successful completion of the deliverables.
WP3 has reached all its main objectives for the RP2 reporting period. The activities have been carried out as planned and the was only a deviation “Humidity tests take much longer than expected and planned for” and the mitigation measure applied has been to continue with the testing beyond the end of the project to squeeze out the most from the valuable samples.
WP4 has reached all its main objectives for the RP2 reporting period. In specific: AALTO and ARAMIS finalized the development of a method for determining cost-efficient maintenance schedules for multi-component systems in the presence of economic and structural dependencies between components. Specifically, the dependencies are modeled as a directed graph whose nodes represent maintenance actions, arcs depict structural dependencies, and weights attached to arcs represent the costs of corresponding maintenance actions. AALTO and ARAMIS developed a method for a systematic and rationale decision making on the selection of the AI algorithms to guide the PHM analysts toward the solutions with the largest expected performance. ARAMIS, POLIMI and RISE enhanced the development of PdM approaches.
WP5 aimed to ensure that the project results & outputs are disseminated widely and effectively exploited by their target groups.
The project has demonstrated commendable progress and achievements across various WPs. Efficient management and coordination during period 2 (WP6) ensured the execution of common consortium activities. While WP1 encountered risks and deviations, strategic mitigation measures were applied, necessitating a project extension and budget shifts. WP2 faced challenges, including technical complexities and resource constraints, yet the team's problem-solving approach led to the successful completion of goals within the broader project scope. WP3 achieved its objectives, with only a deviation in humidity test duration, addressed by extending testing beyond the project's end. WP4 showcased significant accomplishments, with AALTO and ARAMIS developing methods for cost-efficient maintenance schedules and systematic decision-making on AI algorithm selection. PdM approaches were enhanced by ARAMIS, POLIMI, and RISE. Throughout the project, WP5 played a crucial role in disseminating results and ensuring effective exploitation among target groups.
