|
|
KNN Modellierung und Steuerung der Produktion mit künstlichen neuronalen Netzen An adaptive neural network system was developed to be used in firms that follow the workshop principle - handling workpieces at different work stations. This system controls the throughput time and the buffer inventory. Neural networks are able to learn new, non-linear forms of control of production systems. At the same time, they can flexibly adapt themselves to changing production conditions, which are caused by disturbances. The use of neural networks leads to an increase in production efficiency, particularly due to the constant production level, by decreasing the throughput times, minimising the floating capital and having a better control over the disturbances. Contact persons: S. Oelker   Funded by: DFG Duration: 01.01.2000 - 31.12.2003 See project's publications List all projects |
