Distributed Real-time Scheduling for Flexible Manufacturing

Real-time Scheduling of a Flexible Manufacturing System using a Two-phase Machine Learning Algorithm

The static and analytic scheduling approach is very difficult to follow and is not always applicable in real-time. Most of the scheduling algorithms are designed to be established in offline environment. However, we are challenged with three characteristics in real cases: First, problem data of jobs are not known in advance. Second, most of the shop’s parameters tend to be stochastic. Third, th...

Flexible Maximum Urgency First Scheduling for Distributed Real-Time Systems

Optimal distributed real-time scheduling of flexible manufacturing networks modeled as hybrid dynamical systems

The paper considers a class of flexible manufacturing networks. We employ hybrid dynamical systems to model such networks. The main and new achievement of the paper is that we propose a distributed implementable in real time scheduling rule such that the corresponding closed-loop system is stable and optimal. In stable systems the processes converge to periodic ones. The paper gives computing r...

Real-Time Control of Distributed Large Scale Flexible Manufacturing

Due to the ever-increasing computational capabilities and the increasing use of automated manufacturing, distributed large-scale, discrete-event manufacturing system controllers are being proposed and designed. Currently there is a large amount of research in the area of simulation of manufacturing systems, scheduling and some research in the control of automated manufacturing plants. Even inte...

A Neural Network Based Decision Support System for Real-Time Scheduling of Flexible Manufacturing Systems

The objective of this study is to develop a neural network based decision support system for selection of appropriate dispatching rules for a real-time manufacturing system, in order to obtain the desired performance measures given by a user, at different scheduling periods. A simulation experiment is integrated with a neural network to obtain the multi-objective scheduler, where simulation is ...