In production systems, input materials (educts) pass through multiple sequential stages until they become a product. The production stages consist of different machines with various dynamic characteristics. The coupling of those machines is a non-linear distributed system. With a distributed control system based on a multi-agent approach, the production system can achieve (almost) maximum output, where lot size and lot sequence are the most important control variables. In most production processes high throughput and low stock are conflicting goals. In order to compare and compensate between these multiple goals, a fuzzy decision making approach is employed here that decides about the material flow and machine states, based on variables like working load of order queue length.
@article{urn:eudml:doc:39270,
title = {Distributed fuzzy decision making for production scheduling.},
journal = {Mathware and Soft Computing},
volume = {11},
year = {2004},
pages = {211-224},
zbl = {1129.90319},
language = {en},
url = {http://dml.mathdoc.fr/item/urn:eudml:doc:39270}
}
Runkler, Thomas A.; Sollacher, Rudolf; Reverey, Wendelin. Distributed fuzzy decision making for production scheduling.. Mathware and Soft Computing, Tome 11 (2004) pp. 211-224. http://gdmltest.u-ga.fr/item/urn:eudml:doc:39270/