Fraunhofer IIS Supply Chain Services Working Group

Together with the Supply Chain Services working group at Fraunhofer IIS, we have been researching issues relating to artificial intelligence in intralogistics since July 2022. To turn data into usable information, business processes need to be fundamentally rethought. These findings are helping us to further develop our SuPCIS-L8 warehouse management software.

Facts

• Founded in 1995

For more than 2 decades, the Fraunhofer Institute for Integrated Circuits' Supply Chain Services working group has been generating essential information from data. In the departments of the working group, not only are data rooms and IoT prototypes designed for this purpose, but state-of-the-art data analytics methods and innovation tools are also developed further, with which the organizational and strategic digital transformation in the company can succeed.

Following the vision of "success and added value through data", the working group uses and processes data along all relevant business processes in the company and further expands the competencies of its own organization. This scientific expertise, combined with a data pool from almost 25 years of research work and the special infrastructure such as the ADA-Lovelace Center for Analytics, Data and Applications, makes the SCS working group the first point of contact for all questions relating to the successful handling of data.

From the perspective of the Supply Chain Management Working Group, it takes:

• Data rooms and IoT solutions for networked overall systems, in which data is processed independently of its original application and system reference and is thus available in a portable form,
• Analytics methods and procedures in the field of artificial intelligence that turn seemingly unmanageable data volumes and materials into manageable qualitative data and information, and
• Business models and organizations that allow a change of perspective by taking into account upcoming trends, technological opportunities and the human factor in equal measure.