Machine number, priority rule, and due date determination in flexible manufacturing systems using artificial neural networks
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...
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Veröffentlicht in: | Computers & industrial engineering 2006-05, Vol.50 (1), p.185-194 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 0360-8352 1879-0550 |
DOI: | 10.1016/j.cie.2006.02.002 |