Cluster of Excellence – CoE - Self-optimizing production planning and control

 


Cluster of Excellence – CoE - Self-optimizing production planning and control

Content
Today‘s production processes are characterized by increasing customer orientation, higher product variety and more complex material flows. To keep up with the increasing dynamics within the production, the production control has to ensure a robust production process. The required frequency of plan amendments and control interventions require self-optimizing control loops, otherwise late interventions based on outdated data are conducted.

Research questions
In order to increase the future quality of production planning and control and to adapt to the increased demands regarding frequency of adjustments and reaction time, this research project is developing a self-optimizing production plan and control. In the first step, a monitoring system is needed, which conducts a continuous comparison between the planning results of the IT system and the real material flows on the shop floor and identifies any discrepancies. Besides the comparison of the IT system and the real material flows, the monitoring system is also capable of pointing out simulation based production control potential based on feedback data. These potentials are displayed to the employee as control proposals to improve the logistic objectives. The employee then has the option to adapt the IT system as well as the processes on the shop floor accordingly. The employee remains in control and is solely supported by the user-friendly, interactive visualizations.

Results
The result of the research project is a simulation software which automatically builds a simulation model based on the feedback data from the production. If for example predetermined target lead times are exceeded, the tool simulates alternative control procedures and proposes superior control configurations. Further information about the consortium and the demonstrator can be found at
http://www.produktionstechnik.rwth-aachen.de

Sponsor
DFG – German Research Foundation

Acknowledgements and project sponsors
We thank the DFG for the support
Project period: 01.11.1012 – 31.10.2017



Contact:
Melanie Luckert, M.Sc.
Email: m.luckert@wzl.rwth-aachen.de
Tel. 0241 80 28367