About the Project

Project Information

Project title: Data-driven Methods and Tools for Design Innovation (DATA-MATION)
Funding body: Croatian Science Foundation
Project number: IP-2022-10-7775
Institution: University of Zagreb Faculty of Mechanical Engineering and Naval Architecture
Project start date: 18th December 2023
Duration: 48 months
Total funding: 152.900,00 EUR
Contact: [email protected]

Project Objective

The objective of the DATA-MATION project is to develop a research framework for experimental studies of the data-driven design paradigm within engineering design and development projects. The specific research focus will be aimed at studying AI tools to support design automation and new frontiers of AI approaches for design analytics, with the goal of fostering human-machine creativity and decision-making in innovation-oriented product and service development projects. For the project, we have defined five specific research objectives (O1-O5):

  • O1 Understanding the problem field, state-of-the-art review of theory and practice and project scope refinement
  • O2 Development and application of data-driven design experimental research framework
  • O3 Development and application of data-driven design support tools
  • O4 Experimentation with the data-driven design support tools in innovation-oriented product development activities
  • O5 Research validation and definition of future research directions
Expected Results

The project will contribute to both the theory and practice of data-driven design by bringing together interdisciplinary empirical research, conceptualization, and modeling approaches. The results of the proposed project will generate new ideas, findings, and knowledge, which can be transferred to interested representatives of the academic and industrial community and foster further transition to digital society and development of the EU’s innovation potential in this context.

Expected Impact

Impact that the research and acquired scientific competencies and skills will have on potential beneficiaries appears in three ways:

  1. It will enable them to better understand and manage the data-driven design paradigm to address pressing needs for more efficient design and development of products and services.
  2. It will enable them to test and validate the suitability and applicability of AI methods and tools within the context of engineering design.
  3. It will showcase how AI support methods and tools should be contextualized and tailored for the various design activities in a structured manner.