Prediction of surface roughness in CNC face milling using neural networks and Taguchi's design of experiments
Citations
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Cites methods from "Prediction of surface roughness in ..."
...ANN modeling was also used along with designed experiments by Benardos and Vosniakos [47] in face milling....
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...E-mail address: vosniak@central.ntua.gr (G.-C. Vosniakos)....
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Cites methods from "Prediction of surface roughness in ..."
...These approaches can be generally categorized as follows: (i) Empirical or statistical methods that are used to study the effect of internal parameters and choose appropriate values for them based on the performance of model (Benardos & Vosniakos, 2002; Ma & Khorasani, 2003)....
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Cites background or methods from "Prediction of surface roughness in ..."
...The table shows research works based on full factorial designs [29, 54, 62, 68, 69], Taguchi’s orthogonal arrays [ 8 , 70] and response surface designs [71]....
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...Research issues in monitoring machining systems based on artificial intelligence (AI) process models cover several topics, such as sensor system selection [1, 2], multi-sensor and sensor-fusion systems [1, 3, 4], signal processing and sensory feature selection/extraction [5, 6], design of experiments [7, 8 ] and AI techniques to model the process [1, 9]. In spite of the intensive research being carried out in this field, there is still no ......
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...Hence, cutting-force monitoring is frequently used to diagnose/predict both tool condition [5, 16–18] and part accuracy [7, 8 , 19, 20]....
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...Tool breakage detection [18] Surface roughness prediction [7, 8 , 19] Dimensional part accuracy prediction [19, 20]...
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...Benardos [ 8 ] also reported similar conclusions, and it was confirmed experimentally that the X components of cutting forces were the most significant descriptors for surface roughness modelling....
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References
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