IC15 – KIIng

Quality management methods play a crucial role in eliminating errors and reducing costs during production. However, the extensive time and resources required to implement these methods pose a challenge for many small and medium-sized enterprises (SMEs). The use of AI-based approaches has the potential to reduce the efforts involved in quality management. This requires extensive data on products and production processes, which often exists in inconsistent format and contents varying information at different manufacturing SMEs.

Aim and approach

The aim of the project is to gain a comprehensive understanding of the data situation in SMEs and to identify potential requirements and challenges in the integration of AI-based approaches in quality management.

• The project will first examine the data situation at manufacturing SMEs in Baden-Württemberg with regard to the type of data, format and information content.
• Based on this, requirements for the use of AI will be defined in order to increase the efficiency and benefit of knowledge-based quality methods.
• It will be examined whether the existing data is sufficient or whether more data is needed.
• In addition, other value-adding use cases are to be explored.
• In terms of extracting relevant information and closing knowledge gaps, the project also explores how information from drawings can be transferred into knowledge.
• Finally, a guide for SMEs will be developed to help them manage data and prepare for the use of AI.

Benefit

This is expected to promote the widespread use of quality management methods among SMEs to reduce the quality-related cost and strengthen their competitiveness.