Title :
High order neural networks to control manufacturing systems-a comparison study
Author :
Rovithakis, George A. ; Gaganis, Vassilis I. ; Perrakis, Stelios E. ; Christodoulou, Manolis A.
Author_Institution :
Dept. of Electron. & Comput. Eng., Tech. Univ. of Crete, Chania, Greece
Abstract :
In this paper the neuro adaptive scheduling methodology is evaluated by comparing its performance with conventional schedulers, through simulation studies. The case study chosen constitutes an existing manufacturing cell, which can be viewed as a highly complex nonacyclic FMS, with extremely heterogenous part processing times. The results reveal superiority of our algorithm in terms of backlogging and inventory cost, system stability and work-in-process
Keywords :
adaptive systems; computer aided production planning; neural nets; production control; WIP; backlogging cost; heterogenous part processing times; high-order neural networks; highly complex nonacyclic FMS; inventory cost; manufacturing cell; manufacturing system control; neuro adaptive scheduling methodology; system stability; work-in-process; Buffer storage; Control systems; Job shop scheduling; Manufacturing processes; Manufacturing systems; Neural networks; Production; Raw materials; Scheduling algorithm; Testing;
Conference_Titel :
Decision and Control, 1998. Proceedings of the 37th IEEE Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
0-7803-4394-8
DOI :
10.1109/CDC.1998.757868
