Development of interdisciplinary assessment for manufacturing and design
DIAS develop and demonstrate the integrated multidisciplinary tools necessary to speed up implantation and design integration or Open Rotor structural components in next generation aircrafts. This require more flexible design studies, allowing a wider set of design variants to be explored simultaneously with accounting for manufacturing equipment and process applicability. 
DIAS bring in state of the art modelling and simulation techniques for robot path assessment, geometrical variation of weld assembly using advanced modelling software and combines these with architectural modelling tools (CCM, CAM) that allow impact assessment on system level, risk and cost to be included in the same study 
The studies are conduced as evolving and digital design of experiments first outlining the desired design space, identifying feasible regimes of the design space and generate variations of geometries and manufacturing technologies. The results from the simulations are used together with already existing data from Clean Sky high fidelity simulations and experiments to form validated surrogate models. Decision makers and specialist from multiple domains team up and conduct real time trade off analyses to identify most resilient design. AI and Machine learning algorithms are used to facilitate intelligent and interactive decision support. 
The consortia of Chalmers, Cambridge and FCC have experience form collaborating both with the topic leader and eachother from several preceeding research projects and bring together extensive expertise and experience into the study. The expected outcome is expected to allow the manufacturer to optimize new design and reduce the risk to introduce Clean Sky demonstrated configurations and technologies to be introduced in next generation products. As such, DIAS have a profound impact on realizing the significant potential demonstrated for Open Rotor architectures, while including competitive assessment and risk reducing design capabilities.