DAiProM | Data analytics in production management

Even though some artificial intelligence methods and algorithms have been available for years, they are only becoming usable in industrial practice due to the increased availability of data and computing power. In the operational reality of manufacturing companies, however, there are still some obstacles to the application of AI and machine learning. Often, sufficient expertise is still lacking, prerequisites are unknown, and the potential benefits are difficult to assess.

In order to identify and exploit the potential of AI and machine learning in one's own company, it is helpful to analyze key findings from science and research and transfer them to one's own production and logistics processes. Through suitable data pre-processing, the targeted selection of algorithms, and intensive training and testing of models, the scientific findings can be transferred to the company's own use cases. Using detailed analysis and interpretation of the models and correlations, relevant process parameters and cause-effect relationships can be identified. The knowledge gained then makes it possible to derive explanations and recommendations for action to adapt the processes.

Data Analytics and AI at Fraunhofer IGCV

How can the new AI potentials be made accessible for the own company? The key to the success of Artificial Intelligence in the production lies above all in the combination of application knowledge from production management and production technology as well as Artificial Intelligence and machine learning.

At the Fraunhofer IGCV, these key skills are combined, allowing individual solutions to be developed for a wide range of applications. With its key skills in the areas of engineering, production, and multi-material solutions, the Fraunhofer IGCV combines extensive application knowledge with the latest scientific findings.