Application of a neural-network scheduler on a real manufacturing system

摘要

In this paper a neuro adaptive scheduling methodology approaching machine scheduling as a control regulation problem 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 deterministic job shop with extremely heterogenous part processing times. The results facilitate a thorough assessment of our algorithm in terms of backlogging and inventory cost, system stability, and work in process.