Prediction of tool wear using regression and ANN models in end-milling operation a critical review

Tarkan Erdik; Zekai Şen

doi:10.1007/s00170-008-1758-0

Prediction of tool wear using regression and ANN models in end-milling operation a critical review

Tarkan Erdik^*, Zekai Şen

^*Corresponding author for this work

Department of Civil Engineering

Istanbul Technical University

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

Palanisamy et al. (Int J Adv Manuf Technol Volume 37:29-41, 2008) focus on two different models in their research, namely, regression model (RM) artificial neural network (ANN) for predicting tool wear. The prediction values from RM and ANN models are compared with the experimental values conducted by them. The discussion shall focus on the following four main points that are not considered in the study.

Original language	English
Pages (from-to)	765-766
Number of pages	2
Journal	International Journal of Advanced Manufacturing Technology
Volume	43
Issue number	7-8
DOIs	https://doi.org/10.1007/s00170-008-1758-0
Publication status	Published - Aug 2009

Keywords

ANN
Artificial intelligence
Regression method
Tool wear

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10.1007/s00170-008-1758-0

Cite this

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abstract = "Palanisamy et al. (Int J Adv Manuf Technol Volume 37:29-41, 2008) focus on two different models in their research, namely, regression model (RM) artificial neural network (ANN) for predicting tool wear. The prediction values from RM and ANN models are compared with the experimental values conducted by them. The discussion shall focus on the following four main points that are not considered in the study.",

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AB - Palanisamy et al. (Int J Adv Manuf Technol Volume 37:29-41, 2008) focus on two different models in their research, namely, regression model (RM) artificial neural network (ANN) for predicting tool wear. The prediction values from RM and ANN models are compared with the experimental values conducted by them. The discussion shall focus on the following four main points that are not considered in the study.

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KW - Artificial intelligence

KW - Regression method

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Prediction of tool wear using regression and ANN models in end-milling operation a critical review

Abstract

Keywords

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