Find here the overview of the Success stories
Modern software-intensive systems are rarely built from the ground up for each customer. Instead, they evolve as variants of an existing product. Over time, this can lead to an overwhelming number of configurations that must be tested, but testing all these variants manually or with traditional tools is simply impossible. The XIVT project tackled this challenge by developing 28 specialised methods and tools for testing highly configurable, variant-rich embedded systems.
Additive manufacturing (AM), often known as 3D printing, has moved far beyond rapid prototyping. Yet, adoption is not without hurdles. High capital expenditures, material cost, and the need for specialised skills still limit full-scale implementation. SAMUEL addressed this challenge. Its main objective was to provide AM users with knowledge and to assist stakeholders across the AM workflow, making the process more consistent, reliable and efficient.
IMPACT introduced a revolutionary shift from evidence-based to intelligence-based healthcare. This transition was designed to enhance patient quality of life and improve public health but also to reduce costs and improve the working experience for care providers. By leveraging data intelligence, IMPACT has unlocked new possibilities in personalised diagnosis and treatment planning, minimally-invasive and robotic-assisted surgery, and clinical workflow optimisation.
Whether in factory floors, ergonomics research, or autonomous driving simulations, the need for precise and adaptable human motion modelling has grown exponentially. However, traditional motion simulation approaches require multiple heterogeneous tools, and this fragmentation leads to inefficiencies. Recognising these challenges, MOSIM co-developed an open, modular framework for interactive human motion simulation.
As global trade continues to expand, the pressure on ports to handle increasing cargo volumes efficiently and sustainably is greater than ever. By 2030, European cargo traffic is expected to rise by 50%, but with space limitations, ports must turn to innovation rather than expansion. The I²PANEMA project stepped in to address these challenges by integrating smart Internet of Things (IoT) solutions into port operations.
Building Information Modelling (BIM) is a digital representation of a construction project that is increasingly used by the Architect, Engineering and Construction industry. The BIMy project aims at providing an open collaborative platform for sharing, storing and filtering BIM among different BIM owners/ users and integrating and visualising them in their built and natural environment. BIMy can be seen as an open, generic and secure intermediary vehicle that enables interactions between existing and new applications through a standardised open API platform.
Today’s control of industrial processes is done in a highly centralised and hierarchical manner. Future concepts like component based and collaborative automation require much more distributed control functionalities. To support this development, OPTIMUM addresses enhancing the aspects of distributed control, adaptation of IoT technologies to industrial needs, enhancement of control and assistance applications by context and location awareness as well as common-model based 3D engineering and supervision. Thus it will support partners and industry in general to get ready for Industry 4.0 challenges.
Businesses are currently having to deal with a data set that is more than they can handle. Today’s necessity is not the usage of data analytics, it is the utilisation of combined technologies in which data analytics are executed to make sense out of the data. The scope of the project is to build a universal model for data analytics using Deep Learning on a proposed set of technologies including HPDA environment that fit best to the data provided.
CyberFactory#1 aims at designing, developing, integrating and demonstrating a set of key enabling capabilities to foster optimisation and resilience of the Factories of the Future (FoF). It will address the needs of pilots from Transportation, Automotive, Electronics and Machine manufacturing industries around use cases such as statistical process control, real time asset tracking, distributed manufacturing and collaborative robotics. It will also propose preventive and reactive capabilities to address security and safety concerns to FoF like blended cyber-physical threats, manufacturing data theft or adversarial machine learning.
PIANiSM aims at putting together predictive and prescriptive maintenance techniques to achieve an end-to-end automated manufacturing process and optimise end-to-end manufacturing value chains. To disrupt traditional maintenance processes in manufacturing environments, a sophisticated system is required that covers a wide range of domains such as data science, machine learning, analytics, simulation and real-time processing. PIANiSM will provide related missing analytics techniques and algorithms, introduce new generation of data identification & integration and modelling processes, and try to develop standards to enable more flexible and applicable solutions for manufacturers.
The major goal of the project was to develop a new standard - eFMI®: Functional Mock-up Interface for embedded systems - to exchange physics-based models between modeling and simulation environments with software development environments for electronic control units (ECU), micro controllers or other embedded systems and develop prototype implementations for the whole toolchain from physics-based modeling environments to production code on electronic control units. Enabling advanced control and diagnosis functions based on physics models allows the production code in automotive vehicles to be enhanced and the cost and time for the software development of embedded systems to be reduced.
Due to the very limited resources provided by Internet-of-Things (IoT) nodes, today’s commonly used design approach to trade off development time with software efficiency is not competitive any longer. Therefore, an industry-wide effort is needed to provide measures for fast and efficient IoT software development. The main goal of the COMPACT project is to provide novel solutions for the application-specific and customer-oriented realisation of ultra-small IoT nodes with a focus on software generation for IoT nodes with ultra-small memory footprints and ultralow power consumption.
