High order neural networks to control manufacturing systems-a comparison study
George A. Rovithakis, Vassilis I. Gaganis, Stelios E. Perrakis, M.A. Christodoulou · 2002
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.