Cognition Enhanced, Self-optimising Manufacturing Processes
Improving the contribution of cognition combined with intuition and operating experience is the preferred issue to make sound advances in coping with complexity of coupled systems and approaching the vision of self-optimising production.
Cognition-enhanced, self-optimising manufacturing systems should take into account predefined,
multi-criteria target values and use these to find an optimal operating point autonomously and efficiently. Thus a manufacturing process will be guided reliably at its productivity limits. The multicriteria target values consider economic parameters as well as environmental boundary conditions and ecological parameters (Figure below). This research will contribute to (i) achieving cost-efficient production planning and manufacture as well as (ii) reducing the number of scrapped products to contribute to environmental issues. Further, the development and global control of such manufacturing system, requires (iii) high level training and job profiles. This will be a significant contribution to social factors, as shown in Figure below.
Across the entire product lifecycle, the research work of this area addresses actual product manufacturing
within an order processing sequence. Via clearly defined interfaces as well as similar model structures and optimisation strategies, the generic coupling to and integration into the superordinate production structures will be guaranteed. The most important interfaces in this context are the transitions to product and production planning and product assembly phases. Consequently, This research area addresses the following main research question:How can manufacturing systems be modelled cybernetically and optimised with respect to control technology in order to achieve closed loop controlled and optimised manufacturing processes at a machine control level, which interact with super ordinate control loops of the global production network?
In order to answer this research question, it is necessary to generate, research, integrate and to
validate methods and concepts of all manufacturing processes which (i) differ from each other in their physical mode of operation and (ii) have great relevance for production in high-wage countries. The selected examples are gas metal-arc welding, laser cutting, 5-axis milling, injection moulding, weaving and braiding.Contact
Dr.-Ing. Drazen Veselovac
Laboratory for Machine Tools and Production Engineering (WZL)
Chair of Manufacturing Technology
Steinbachstr. 19, D-52074 Aachen
Phone: +49 (0)241 80-27432 Fax: +49 (0)241 80-22293
d.veselovac@wzl.rwth-aachen.de
Thomas Auerbach
Laboratory for Machine Tools and Production Engineering (WZL)
Chair of Manufacturing Technology
Steinbachstr. 19, D-52074 Aachen
Phone: +49 (0)241 80-28022 Fax: +49 (0)241 80-22293
t.auerbach@wzl.rwth-aachen.de
Coordinator
Prof. Dr.-Ing. Dr-Ing. E.h. Dr. h.c. Dr. h.c. Fritz Klocke
Laboratory for Machine Tools and Production Engineering (WZL)
Chair of Manufacturing Technology
Steinbachstr. 19, D-52074 Aachen
Phone: +49 (0)241 80-27401 Fax: +49 (0)241 80-22359
f.klocke@wzl.rwth-aachen.de
