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| Titel: |
Development of manufacturing control strategies using unsupervised machine learning |
| Auteur: |
Bowden, Royce Bullington, Stanley F. |
| Verschenen in: |
IIE transactions |
| Paginering: | Jaargang 28 (1996) nr. 4 pagina's 319-331 |
| Jaar: |
1996-04-01 |
| Inhoud: |
This research considers the control of manufacturing systems that support job routing and process sequence flexibility. A machine learning system is presented that uses a simulation model of the target manufacturing system to discover opportunistic control rules. Learning is unsupervised and is driven by a genetic algorithm. The learning method requires very little a priori control knowledge. For this presentation, the decision-making agents are the part types being processed. Part types evolve cooperative strategies for selecting the best route through the manufacturing system based on simulated real-time information that describes the state of the system. Results are presented that demonstrate the effectiveness of the approach. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
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