MegaMaRt2 - Megamodelling at Runtime (ECSEL/Vinnova)

Status:

finished

Start date:

2017-04-01

End date:

2020-03-31

 

European industry faces stiff competition on the global arena. Electronic Components and Systems become more and more complex, thus calling for modern engineering practices to be applied in order to better tackle both productivity and quality. Model-based technologies promise significant productivity gains, which have already been proven in several studies and applications. However, these technologies still need more enhancements to scale up for real-life industrial projects and to provide more benefits in different contexts. The ultimate objective of improving productivity, while reducing costs and ensuring quality in development, integration and maintenance, can be achieved by using techniques integrating seamlessly design time and runtime aspects. Industrial scale system models, which are usually multi-disciplinary, multi-teams and serving to several product lines have to be be exploited at runtime, e.g. by advanced tracing and monitoring, thus boosting the overall quality of the final system and providing lessons-learnt for future product generations. MegaM@Rt brings model-based engineering to the next level in order to help European industry reducing development and maintenance costs while reinforcing both productivity and quality. To achieve that, MegaM@Rt will create a framework incorporating methods and tools for continuous development and runtime validation to significantly improve productivity, quality and predictability of large and complex industrial systems. MegaM@Rt addresses the scalability challenges with advanced megamodelling and traceability approaches, while runtime aspects will be tackled via so-called “models@runtime”, online testing and execution traces analysis. MegaM@Rt brings together a strong international consortium involving experts from France, Spain, Italy and Finland. The partners cover the whole value chain from research organizations to tool providers, including 9 end-users with large industrial case studies for results validation.