Grinding Forces Prediction Based Upon Experimental Design and Neural Network Models

Ridha Amamou, Nabil Ben Fredj, Farhat Fnaiech

Abstract

The results presented are related to the prediction of the specific grinding force components. The main problems associated with the prediction capability of empirical models developed using the design of experiment (DOE) method are given. In this study an approach suggesting the combination of DOE method and artificial neural network (ANN) is developed. The inputs of the developed ANNs were selected among the factors and interaction between factors of the DOE depending on their significance at different confidence levels expressed by the value of %. Results have shown particularly, the existence of a critical input set which improves the learning ability of the constructed ANNs. The built ANNs using these critical sets have shown low deviation from the training data and an acceptable deviation from the testing data. A high prediction accuracy of these ANNs was tested between models constructed using the developed approach and models developed by previous investigations.

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Paper Citation


in Harvard Style

Amamou R., Ben Fredj N. and Fnaiech F. (2005). Grinding Forces Prediction Based Upon Experimental Design and Neural Network Models . In Proceedings of the 1st International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2005) ISBN 972-8865-36-8, pages 122-131. DOI: 10.5220/0001194101220131


in Bibtex Style

@conference{anniip05,
author={Ridha Amamou and Nabil Ben Fredj and Farhat Fnaiech},
title={Grinding Forces Prediction Based Upon Experimental Design and Neural Network Models},
booktitle={Proceedings of the 1st International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2005)},
year={2005},
pages={122-131},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001194101220131},
isbn={972-8865-36-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2005)
TI - Grinding Forces Prediction Based Upon Experimental Design and Neural Network Models
SN - 972-8865-36-8
AU - Amamou R.
AU - Ben Fredj N.
AU - Fnaiech F.
PY - 2005
SP - 122
EP - 131
DO - 10.5220/0001194101220131