Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/559754B0-E18B-466F-8062-F8CC97A85528 | ||
| Year | 1999 | ||
| Type of Item | Peer-Reviewed Journal Publication | ||
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| Bibliographic Citation | M. Christodoulou and V. Gaganis, "Neural networks in manufacturing cell design", Computers in Industry, vol. 36, no. 1-2, pp. 133-138, 1998. doi:10.1016/S0166-3615(97)00107-3 https://doi.org/10.1016/S0166-3615(97)00107-3 | ||
| Appears in Collections |
This paper presents a neural network approach in determining the appropriate manufacturing cell configuration that meets the required performance measures. Simulation experiments were conducted with many possible combinations of design changes to calculate cell performance measures, and thus generate training pairs for a neural network. Three different static neural network structures have been trained using the above data. Comparison of neural network efficiency and computational effort required is made through a case study, for every neural network architecture.
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