Author(s): Fernandes, Nuno O. ; Martins, Tiago ; Silva, Sílvio do Carmo
Date: 2018
Persistent ID: http://hdl.handle.net/10400.11/6276
Origin: Repositório Científico do Instituto Politécnico de Castelo Branco
Subject(s): Autonomous production control; Flexible flow shops; Simulation; Autonomous production control; Autonomous production control; Flexible flow shops; Flexible flow shops; Simulation; Simulation
Autonomous Production Control (APC) aims at improving production systems performance through fast and flexible reaction to changes in dynamic environments. In this paper, a new APC method for job routing decision-making is proposed and its performance compared with that of two other APC methods, namely the Queue Length Estimator and the Pheromones, and with two conventional control strategies – a centralized and a random decision-making strategy. A discrete-event simulation model of a flexible flow shop operating under make-to-order was used to evaluate performance. Results show that the new method outperforms those with which it was compared, under high system workload and high variability of orders’ arrival and operation times. The study gives a contribution for better understanding of the performance behavior of APC methods, having important implications for industrial practice and for future research on autonomous production control.
