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.

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