Duration: Completed | 01/2021 – 12/2021
Funded by: European Union
If you have any questions about this completed project please contact our institute management:
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At the current state, applications of artificial intelligence in the production context are only marginally widespread. One of the reasons for this is the lack of knowledge among employees in production-related functions. While there are numerous freely available training materials on the basics of AI, they lack practical relevance. However, even when basic knowledge is available, users are faced with the question of how to ideally complete the implementation of an initial AI application. After all, the implementation process relies heavily on expert knowledge. However, many companies – especially small and medium-sized enterprises – lack such AI experts.
Building on this gap, the project HiAI aims to lower the existing hurdle for the use of artificial intelligence in the production environment. For this purpose, on the one hand, learning material is being developed that is specifically geared to the requirements of shopfloor managers. In addition, a toolbox will be developed to provide practical support for employees during implementation in order to alleviate the shortage of experts.
In a first step, a so-called competence map is developed. It includes the required competencies that are important for the use of AI in one's own production environment. The map also serves as the basis for the learning material that is created in the second step. The content will be distributed online via the EIT learning platform. The learning units will address the following topics, among others: Demonstration of use cases in production, introduction to “AI project management” and interpretation of results. In the second half of the year, the concept of the AI toolbox will then be developed. It will include relevant use cases and successively map the process for implementation, while providing employees with concrete action instructions for implementation.
This project is funded by EIT Manufacturing. We thank for the opportunity to work on this project.