Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
EN
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EL
| URI: | http://purl.tuc.gr/dl/dias/559754B0-E18B-466F-8062-F8CC97A85528 | ||
| Έτος | 1999 | ||
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | ||
| Άδεια Χρήσης |
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| Βιβλιογραφική Αναφορά | 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 | ||
| Εμφανίζεται στις Συλλογές |
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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