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Authors: Menelaos Pappas 1 ; Ioannis Ntziantzias 2 ; John Kechagias 3 and Nikolaos Vaxevanidis 4

Affiliations: 1 Technological Educational Institute of Larissa, Greece ; 2 University of Thessaly, Greece ; 3 Technological Educational Institute of Larissa and University of Thessaly, Greece ; 4 University of Thessaly and School of Pedagogical and Technological Education (ASPETE), Greece

ISBN: 978-989-8425-84-3

Keyword(s): Abrasive Water Jet Machining (AWJM), Artificial Neural Networks (ANN), Taguchi Method, Surface Quality, Process Parameters.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Computer-Supported Education ; Domain Applications and Case Studies ; Fuzzy Systems ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Industrial, Financial and Medical Applications ; Methodologies and Methods ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: This work presents a hybrid approach based on the Taguchi method and the Artificial Neural Networks (ANNs) for the modeling of surface quality characteristics in Abrasive Water Jet Machining (AWJM). The selected inputs of the ANN model are the thickness of steel sheet, the nozzle diameter, the stand-off distance and the traverse speed. The outputs of the ANN model are the surface quality characteristics, namely the kerf geometry and the surface roughness. The data used to train the ANN model was selected according to the Taguchi’s design of experiments. The acquired results indicate that the proposed modelling approach could be effectively used to predict the kerf geometry and the surface roughness in AWJM, thus supporting the decision making during process planning.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Pappas, M.; Ntziantzias, I.; Kechagias, J. and Vaxevanidis, N. (2011). MODELING OF ABRASIVE WATER JET MACHINING USING TAGUCHI METHOD AND ARTIFICIAL NEURAL NETWORKS. In Proceedings of the International Conference on Neural Computation Theory and Applications - NCTA, (IJCCI 2011) ISBN 978-989-8425-84-3, pages 377-380. DOI: 10.5220/0003681103770380

@conference{ncta11,
author={Menelaos Pappas. and Ioannis Ntziantzias. and John Kechagias. and Nikolaos Vaxevanidis.},
title={MODELING OF ABRASIVE WATER JET MACHINING USING TAGUCHI METHOD AND ARTIFICIAL NEURAL NETWORKS},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications - NCTA, (IJCCI 2011)},
year={2011},
pages={377-380},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003681103770380},
isbn={978-989-8425-84-3},
}

TY - CONF

JO - Proceedings of the International Conference on Neural Computation Theory and Applications - NCTA, (IJCCI 2011)
TI - MODELING OF ABRASIVE WATER JET MACHINING USING TAGUCHI METHOD AND ARTIFICIAL NEURAL NETWORKS
SN - 978-989-8425-84-3
AU - Pappas, M.
AU - Ntziantzias, I.
AU - Kechagias, J.
AU - Vaxevanidis, N.
PY - 2011
SP - 377
EP - 380
DO - 10.5220/0003681103770380

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