Ce topic appartient à l'appel HORIZON-JU-CHIPS-2025-IA-two-stage
Identifiant du topic: HORIZON-JU-CHIPS-2025-IA-two-stage-FT2

AI-assisted Methods and Tools for Engineering Automation

Type d'action : HORIZON JU Innovation Actions
Date d'ouverture : 04 mars 2025
Date de clôture 1 : 30 avril 2025 00:00
Date de clôture 2 : 17 septembre 2025 00:00
Budget : €20 000 000
Call : HORIZON-JU-CHIPS-2025-IA-two-stage
Call Identifier : HORIZON-JU-CHIPS-2025-IA-two-stage
Description :

Expected Outcome:

The project is expected to contribute to the following outcomes:

  • Advanced AI-assisted methods and tools, including generative AI, for the automation of software engineering tasks, from enhancing human efficiency and optimizing resource utilization to enabling complex data/problems analysis/interpretation and supporting intelligent decision-making. Such engineering tasks often involve multiple domains (e.g., modelling, control, data management, communication, mechatronics, etc.) and stakeholders, with the burden of daunting legacy integration, refactoring (e.g., to re-design and replace obsolete technology), and the compliance with specific standards, regulations and certifications.
  • Open and extensible AI-assisted integrated platform, based on methodologies including AI-support, AI-based tools and toolchains, following a well-defined engineering process, including the integration with legacy tools. The platform shall provide flexible usage in small and large multi-domain and multi-stakeholder engineering teams, impacting existing and upcoming ECS engineering automation tools and their usage.
  • Showcasing and evaluation for software-defined vehicles of efficiency enhancements in terms of cost and time for complex data/knowledge management, resource optimization, energy consumption, interoperability, product/process quality/trustworthiness, learning curve and usability, over the whole lifecycle, from design, through deployment, operations, and maintenance, to the product end-of-life and recycling, and its evolution.
  • Best practices and small proof-of-concept studies for other sectors, e.g. medical/pharmaceutical and/or digital industry.