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Surface roughness of Ti6Al4V after heat treatment evaluated by artificial neural networks

  • Assist. Prof. Dr. Mehmet Altuğ, born 1978, received his BSc from University of Gazi, Faculty of Tech. Education, Ankara, Turkey in 2002 and his MSc in 2003. In 2010, he completed his PhD at the same university and since 2011 he has been working as Assistant Professor at Inonu University, Malatya, Turkey. His research areas include WEDM, rapid prototyping, manufacturing technology, production techniques, Taguchi method, and artificial neural networks as well as genetic algorithm.

     EMAIL logo     ,

    Assist. Prof. Dr. Mehmet Erdem, born 1975, received his BSc from University of Marmara, Faculty of Tech. Education, İstanbul, Turkey in 1997 and his MSc from Gazi University, Ankara,Turkey in 2001. In 2007, he completed his PhD at the same university and since 2012 he has been working as Assistant Professor at Inonu University, Malatya, Turkey. His research areas include, metallurgical process, WEDM, manufacturing technology, production techniques, Taguchi method, and artificial neural networks as well as genetic algorithm.

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    Assist. Prof. Dr. Cetin Ozay, born 1978, received his BSc from University of Firat, Faculty of Tech. Education, Elazig, Turkey in 2000 and his MSc in 2004. In 2009, he completed his PhD at the same university and since 2011 he has been working as Assistant Professor. His research areas include turn-milling, manufacturing technology, production techniques, Taguchi method, and artificial neural networks as well as genetic algorithm.

         and

    Associate Prof. Dr. Oğuz Bozkır, born 1955, received his BSc from University of Yıldız Technical University, Faculty of Engineering, İstanbul, Turkey in 1981 and his MSc from Fırat University, Turkey in 1994. In 2002, he completed his PhD at Erciyes University, Turkey and since 1990 he has been working as Associate Professor at Inonu University, Malatya, Turkey. His research areas include WEDM, manufacturing technology, production techniques, Taguchi method and artificial neural networks.
Published/Copyright: March 7, 2022
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Materials Testing
From the journal Materials Testing Volume 58 Issue 3

Abstract

The study examines how, using wire electrical discharge machining (WEDM), the microstructural, mechanical and conductivity characteristics of the titanium alloy Ti6Al4V are changed as a result of heat treatment and the effect they have on machinability.Scanning electron microscope (SEM), optical microscope and X-ray diffraction (XRD) examinations were performed to determine various characteristics and additionally related microhardness and conductivity measurements were conducted. L18 Taquchi test design was performed with three levels and six different parameters to determine the effect of such alterations on its machinability using WEDM and post-processing surface roughness (Ra) values were determined. Micro-changes were ensured successfully by using heat treatments. Results obtained with the optimization technique of artificial neural network (ANN) presented minimum surface roughness. Values obtained by using response surface method along with this equation were completely comparable with those achieved in the experiments. The best surface roughness value was obtained from sample D which had a tempered martensite structure.

Abstract

In der diesem Beitrag zugrunde liegenden Studie wurde untersucht wie, unter Anwendung des Drahterodierens (Wire Electrical Discharge Machining (WEDM)), die mikrostrukturellen sowie die mechanischen Eigenschaften und Leitfähigkeitseigenschaften der Titanlegierung Ti6Al4V nach Wärmebehandlung verändert werden und welche Auswirkungen diese auf die maschinelle Bearbeitbarkeit haben. Es wurden Untersuchungen mit dem Rasterelektronenmikroskop, dem Lichtmikroskop und mittels Röntgendiffraktometrie durchgeführt, um die verschiedenen Charakteristika zu ermitteln, darüber hinaus wurden zusätzlich entsprechende Mikrohärte- und Leitfähigkeitsmessungen durchgeführt. Hierzu wurde ein L18 Taguchi Versuchsdesign angewendet, und zwar mit drei Ebenen und sechs verschiedenen Parametern, um die Auswirkungen solcher Veränderungen auf die Bearbeitbarkeit mittels WEDM und die entsprechende Oberflächenrauheitswerte Ra nach einer solchen Behandlung zu bestimmen. Mit der Wärmebehandlung wurden erfolgreich für entsprechende Mikroveränderungen gesorgt. Die Resultate aus der Optimierungstechnik mit künstlichen neuronalen Netzen ergaben eine minimale Oberflächenrauheit. Die Werte, die mit dem Oberflächenantwortverfahren zusammen mit dieser Gleichung ermittelt wurden, waren vollständig vergleichbar mit denen, die sich aus den Experimenten ergaben. Die besten Oberflächenrauheiten ergaben sich für die Probe D, die einen angelassenen Martensit als Gefüge aufwies.

Keywords: Ti6Al4V; heat treatment; WEDM; surface roughness; artificial neural network
Assist. Prof. Dr. Mehmet Altuğ Department of Machine and Metal Technologies Malatya Vocational High School Inonu University, Inönü cd. No. 192/7 Malatya, Turkey

About the authors

Assist. Prof. Dr. Mehmet Altuğ

Assist. Prof. Dr. Mehmet Altuğ, born 1978, received his BSc from University of Gazi, Faculty of Tech. Education, Ankara, Turkey in 2002 and his MSc in 2003. In 2010, he completed his PhD at the same university and since 2011 he has been working as Assistant Professor at Inonu University, Malatya, Turkey. His research areas include WEDM, rapid prototyping, manufacturing technology, production techniques, Taguchi method, and artificial neural networks as well as genetic algorithm.

Assist. Prof. Dr. Mehmet Erdem

Assist. Prof. Dr. Mehmet Erdem, born 1975, received his BSc from University of Marmara, Faculty of Tech. Education, İstanbul, Turkey in 1997 and his MSc from Gazi University, Ankara,Turkey in 2001. In 2007, he completed his PhD at the same university and since 2012 he has been working as Assistant Professor at Inonu University, Malatya, Turkey. His research areas include, metallurgical process, WEDM, manufacturing technology, production techniques, Taguchi method, and artificial neural networks as well as genetic algorithm.

Assist. Prof. Dr. Cetin Ozay

Assist. Prof. Dr. Cetin Ozay, born 1978, received his BSc from University of Firat, Faculty of Tech. Education, Elazig, Turkey in 2000 and his MSc in 2004. In 2009, he completed his PhD at the same university and since 2011 he has been working as Assistant Professor. His research areas include turn-milling, manufacturing technology, production techniques, Taguchi method, and artificial neural networks as well as genetic algorithm.

Associate Prof. Dr. Oguz Bozkır

Associate Prof. Dr. Oğuz Bozkır, born 1955, received his BSc from University of Yıldız Technical University, Faculty of Engineering, İstanbul, Turkey in 1981 and his MSc from Fırat University, Turkey in 1994. In 2002, he completed his PhD at Erciyes University, Turkey and since 1990 he has been working as Associate Professor at Inonu University, Malatya, Turkey. His research areas include WEDM, manufacturing technology, production techniques, Taguchi method and artificial neural networks.

Acknowledgement

This study was supported by Inonu University Scientific Researches Projects with number 2012/165. We thank the Rectorate of Inonu University, Malatya, Turkey for its support.

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Published Online: 2022-03-07

© 2016 Carl Hanser Verlag, München

Articles in the same Issue

  1. Contents
  2. Mechanical Testing
  3. Deformation and damage behavior of lightweight steels at high rate multiaxial loading
  4. Failure Analysis
  5. Reheat cracking failure of a welded alloy 803 outlet pigtail tube used in a steam hydrocarbon reforming furnace
  6. Production-Oriented Testing
  7. Surface roughness of Ti6Al4V after heat treatment evaluated by artificial neural networks
  8. Fatigue life of the magnesium alloy AZ31B under specific spectrum loading
  9. Mechanical Testing
  10. Optimization of welding parameters to attain maximum strength in friction stir welded AA7075 joints
  11. Experimental investigations of Al-TiO2-Gr hybrid composites fabricated by stir casting
  12. Corrosion Testing/Failure Analysis
  13. Microstructure investigation of premature corroded heat exchanger plates
  14. Mechanical Testing
  15. Investigation of deep-drilled micro-hole profiles in Hadfield steel
  16. Wear Testing
  17. Investigation of the abrasive wear behavior of an aluminum alloy and its Al2O3 particle reinforced composite by statistical analysis
  18. Production-Oriented Testing
  19. Optimization of process parameters for rectangular cup deep drawing by the Taguchi method and genetic algorithm
  20. Fabrication of microstructured polymers by a simple biotemplate embossing method and their characterization
  21. Fatigue testing/fractography/materialography
  22. Performance of non-asbestos organic brake liners for light motor vehicles
  23. Failure Analysis
  24. Material optimization of a cemented tibia tray using functionally graded material
  25. Mechanical Testing
  26. Effect of agglomeration and dispersion on the elastic properties of polymer nanocomposites: A Monte Carlo finite element analysis
  27. Production-Oriented Testing
  28. Effects of machining parameters and reinforcement content on thrust force during drilling of hybrid composites
https://doi.org/10.3139/120.110844
Keywords for this article
Ti6Al4V; heat treatment; WEDM; surface roughness; artificial neural network

Articles in the same Issue

  1. Contents
  2. Mechanical Testing
  3. Deformation and damage behavior of lightweight steels at high rate multiaxial loading
  4. Failure Analysis
  5. Reheat cracking failure of a welded alloy 803 outlet pigtail tube used in a steam hydrocarbon reforming furnace
  6. Production-Oriented Testing
  7. Surface roughness of Ti6Al4V after heat treatment evaluated by artificial neural networks
  8. Fatigue life of the magnesium alloy AZ31B under specific spectrum loading
  9. Mechanical Testing
  10. Optimization of welding parameters to attain maximum strength in friction stir welded AA7075 joints
  11. Experimental investigations of Al-TiO2-Gr hybrid composites fabricated by stir casting
  12. Corrosion Testing/Failure Analysis
  13. Microstructure investigation of premature corroded heat exchanger plates
  14. Mechanical Testing
  15. Investigation of deep-drilled micro-hole profiles in Hadfield steel
  16. Wear Testing
  17. Investigation of the abrasive wear behavior of an aluminum alloy and its Al2O3 particle reinforced composite by statistical analysis
  18. Production-Oriented Testing
  19. Optimization of process parameters for rectangular cup deep drawing by the Taguchi method and genetic algorithm
  20. Fabrication of microstructured polymers by a simple biotemplate embossing method and their characterization
  21. Fatigue testing/fractography/materialography
  22. Performance of non-asbestos organic brake liners for light motor vehicles
  23. Failure Analysis
  24. Material optimization of a cemented tibia tray using functionally graded material
  25. Mechanical Testing
  26. Effect of agglomeration and dispersion on the elastic properties of polymer nanocomposites: A Monte Carlo finite element analysis
  27. Production-Oriented Testing
  28. Effects of machining parameters and reinforcement content on thrust force during drilling of hybrid composites
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