Self-learning control of cross-technology matrix production using simulation-based AI

Planning of a flexible production system for coating technology.
© Fraunhofer IST
Planning of a flexible production system for coating technology.

Challenge  

Manufacturing companies are confronted with a high number of variants from customers, fluctuating demand and low market predictability. In addition, they operate in a global competitive environment that calls for products which are not only innovative and cost-effective but also manufactured in an increasingly sustainable manner.

Solution 

Matrix production as a resilient production system enables the economic manufacturing of complex products with simultaneous variant flexibility and scalability in volatile environments. The focus of the project is directed at a holistic view of the production system instead of a flexible but singular machine and plant control and encompasses the material provision, the continuous optimization of the system, the monitoring of key performance indicators, the control of driverless transport vehicles, the integration of alternative technology capabilities and the communication between individual elements. At the Fraunhofer IST, the results are to be incorporated into the planning of a versatile production system which will represent a coating process which is flexible in terms of unit numbers and variants. 

Added value

The vision of SE.MA.KI is the further development of the resilient approach for increasing application maturity by empowering humans and systems to plan and operate the system as well as the integration of high-tech equipment. In the case of coating technology, the range of applications will be increased on the basis of economical, quantity-flexible manufacturing with improved production reliability.

Further information

 

Expert blog

Please find more information on the SE.MA.KI project  on the website of the Fraunhofer Group for Production:

 

Blog post

Flexible production systems for smart surfaces

Funding reference

 

 

This project is funded by the German Federal Ministry of Education and Research.

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