Machine number, priority rule, and due date determination in flexible manufacturing systems using artificial neural networks
Computers and Industrial Engineering, vol.50, no.1-2, pp.185-194, 2006 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 50 Issue: 1-2
- Publication Date: 2006
- Doi Number: 10.1016/j.cie.2006.02.002
- Journal Name: Computers and Industrial Engineering
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
- Page Numbers: pp.185-194
- Keywords: Artificial neural networks, Due date assignment, Flexible manufacturing system, Inverse scheduling, Priority rules
- Istanbul Gelisim University Affiliated: No
Abstract
When there is a production system with excess capacity, i.e. more capacity than the demand for the foreseeable future, upper management might consider utilizing only a portion of the available capacity by decreasing the number of workers or halting production on some of the machines/production lines, etc. while preserving the flexibility of the production system to satisfy demand spikes. To achieve this flexibility, upper management might be willing to attain some pre-determined/desired performance values in a production system having identical parallel machines in each work center. In this study, we propose a framework that utilizes parallel neural networks to make decisions on the availability of resources, due date assignments for incoming orders, and dispatching rules for scheduling. This framework is applied to a flexible manufacturing system with work centers having parallel identical machines. The artificial neural networks were able to satisfactorily capture the underlying relationship between the design and control parameters of a manufacturing system and the resulting performance targets. © 2006 Elsevier Ltd. All rights reserved.