Scientific Research and Essays

  • Abbreviation: Sci. Res. Essays
  • Language: English
  • ISSN: 1992-2248
  • DOI: 10.5897/SRE
  • Start Year: 2006
  • Published Articles: 2732

Full Length Research Paper

On-line prediction of tool wears by using methods of artificial neural networks and fuzzy logic

Fatih Başçiftçi1 and Hüseyin Şeker2
  1Department of Electronics and Computer Education, Technical Education Faculty, Selcuk University, 42003, Selçuklu, Konya/Turkey. 2Master Student of Graduate School of Natural and Applied Sciences, Selcuk University, Konya/Turkey.
Email: [email protected]

  • Article Number - 864B58016736
  • Vol.5(19), pp. 2883-2888, October 2010
  •  Accepted: 30 September 2010
  •  Published: 04 October 2010

Abstract

 

The goal of this study is prediction of tool wear with integrated system made by on-line monitoring of the changes on tool during cutting operations with using artificial neural networks and fuzzy logic methods. For best monitoring, the tool condition, multiple sensor data are collected to represent the tool condition. Artificial neural networks with different parameters was first trained with sample experimental data and then tested with test data. Fuzzy logic is used for the classification of tool wear which is estimated with neural network according to the predefined levels. Results with 100% accuracy are gained by fuzzy process in predefined classes. The software written for this study can be used to monitor tool condition on-line, saving sensor data, viewing the process on graphic and producing alarm-control signals when it is necessary.

 

Key words: Tool condition monitoring, artificial neural networks, fuzzy logic, tool wear, turning.

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