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Comparison of ANN and DoE for the prediction of laser machined micro-channel dimensions

Karazi, Shadi and Brabazon, Dermot and Issa, Ahmed A.A. (2009) Comparison of ANN and DoE for the prediction of laser machined micro-channel dimensions. Optics and Lasers in Engineering, 47 (9). pp. 956-964. ISSN 0143-8166

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This paper presents four models developed for the prediction of the dimensions of laser formed micro-channels. Artificial Neural Networks (ANNs) are often used for the development of predictive models. Three feed-forward, back-propagation ANN models varied in terms of the number and the selection of training data, were developed. These ANN models were constructed in LabVIEW coding. The performance of these ANN models was compared with a 33 statistical design of experiments (DoE) model built with the same input data. When compared with the actual results two of the ANN models showed greater prediction error than the DoE model. The other ANN model showed an improved predictive capability that was approximately twice as good as that provided from the DoE model.

Item Type:Article (Published)
Uncontrolled Keywords:ANN; DoE; laser micro-machining; prediction modelling; parameter selection; channel dimensions;
Subjects:Engineering > Mechanical engineering
Mathematics > Statistics
Computer Science > Artificial intelligence
Physical Sciences > Lasers
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Mechanical and Manufacturing Engineering
Official URL:
Copyright Information:Copyright © 2009 Elsevier Ltd
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:15039
Deposited On:03 Dec 2009 11:58 by Shadi Karazi. Last Modified 25 Nov 2016 16:29

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