SURFACE ROUGHNESS MODELLING AND OPTIMIZATION IN CNC END MILLING USING TAGUCHI DESIGN AND NEURAL NETWORKS
Menelaos Pappas, John Kechagias, Vassilis Iakovakis, Stergios Maropoulos
2011
Abstract
A Neural Network modelling approach is presented for the prediction of surface texture parameters during end milling of aluminium alloy 5083. Eighteen carbide end mill cutters were manufactured by a five axis grinding machine and assigned to mill eighteen pockets having different combinations of geometry parameters and cutting parameter values, according to the L18 (21x37) standard orthogonal array. A feed-forward back-propagation NN was developed using data obtained from experimental work conducted on a CNC milling machine center according to the principles of Taguchi’s design of experiments method. It was found that NN approach can be applied easily on designed experiments and predictions can be achieved, fast and quite accurately.
References
- Chryssolouris, G., Pappas, M., Karabatsou, V., 2004. Posture based discomfort modeling using neural networks. Proceedings of IFAC MIM'04, Athens, Greece, 19-23.
- Engin, S., Altintas, Y., 2001. Mechanics and dynamics of general milling cutters: Part I: helical end mills. Int. J. Mach. Tools Manu. 41(15), 2195-2212.
- Kechagias, J., Iakovakis, V., 2009. A neural network solution for LOM process performance. Int. J. Advanced Manufacturing Technology, 43(11-12), 1214-1222.
- Kechagias J., Pappas, M., Karagiannis, S., Petropoulos, G., Iakovakis, V., Maropoulos, S., 2010. An ANN Approach on the Optimization of the Cutting Parameters During CNC Plasma-Arc Cutting, Proceedings of ASME ESDA 2010, Istanbul, Turkey.
- Kechagias, J., Petropoulos, G., Iakovakis, V., Maropoulos, S., 2009. An investigation of surface texture parameters during turning of a reinforced polymer composite using design of experiments and analysis. Int. J. Experimental Design and Process Optimisation. 1(2/3), 164-177.
- Markopoulos, A., et al., 2006. Artificial neural networks modeling of surface finish in electro-discharge machining of tool steels. Proceedings of ASME ESDA 2006, Torino, Italy.
- Phadke, M. S., 1989. Quality Engineering using Robust Design. Prentice-Hall, Englewood Cliffs, NJ.
- Prechelt, L., 1998. Automatic early stopping using cross validation: quantifying the criteria. Neural Networks, 11(4), 761-767.
- Tzafestas, S. G., et al., 1996. On the overtraining phenomenon of backpropagation NNs. Mathematics and Computers in Simulation, 40, 507-521.
- Yun, W. S., Cho, D. W., 2000. An improved method for the determination of 3D cutting force coefficients and runout parameters in end milling. Int. J. Adv. Manuf. Technol., 16, 851-858.
Paper Citation
in Harvard Style
Pappas M., Kechagias J., Iakovakis V. and Maropoulos S. (2011). SURFACE ROUGHNESS MODELLING AND OPTIMIZATION IN CNC END MILLING USING TAGUCHI DESIGN AND NEURAL NETWORKS . In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8425-40-9, pages 595-598. DOI: 10.5220/0003180505950598
in Bibtex Style
@conference{icaart11,
author={Menelaos Pappas and John Kechagias and Vassilis Iakovakis and Stergios Maropoulos},
title={SURFACE ROUGHNESS MODELLING AND OPTIMIZATION IN CNC END MILLING USING TAGUCHI DESIGN AND NEURAL NETWORKS
},
booktitle={Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2011},
pages={595-598},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003180505950598},
isbn={978-989-8425-40-9},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - SURFACE ROUGHNESS MODELLING AND OPTIMIZATION IN CNC END MILLING USING TAGUCHI DESIGN AND NEURAL NETWORKS
SN - 978-989-8425-40-9
AU - Pappas M.
AU - Kechagias J.
AU - Iakovakis V.
AU - Maropoulos S.
PY - 2011
SP - 595
EP - 598
DO - 10.5220/0003180505950598