Prediction of cutting force in turning of ti-6al-4v under minimum quantity lubrication (Mql) using response surface model and fuzzy logic model

Ravindra R. Malagi, Sanjeevkumar R. Chougula, Ravira J. Shetty

Research output: Contribution to journalArticle

Abstract

Titanium Alloy’s (Ti-6Al-4V) are utilized in many manufacturing fields due to their exclusive properties. Machining of these materials has become a problem for metal cutting industries due to its chemical reaction on tool material. Thus metal cutting industries are looking forward for identifying the optimum cutting parameters during turning of Ti-6Al-4V. Hence in this paper, Response Surface Model and Fuzzy Logic model has been used to estimate and optimize cutting conditions for cutting force during turning ofTi-6Al-4Vunder Minimum Quantity Lubricant condition. From the observations of these two approaches we can conclude that Response Surface Model and Fuzzy Logic model can be effectively used for identifying the optimum cutting parameters and preventing time consuming experiments.

Original languageEnglish
Pages (from-to)263-274
Number of pages12
JournalInternational Journal of Mechanical and Production Engineering Research and Development
Volume8
Issue number6
DOIs
Publication statusPublished - 01-01-2018
Externally publishedYes

Fingerprint

Fuzzy logic
Lubrication
Metal cutting
Titanium alloys
Lubricants
Chemical reactions
Industry
Machining
Experiments

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes

Cite this

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abstract = "Titanium Alloy’s (Ti-6Al-4V) are utilized in many manufacturing fields due to their exclusive properties. Machining of these materials has become a problem for metal cutting industries due to its chemical reaction on tool material. Thus metal cutting industries are looking forward for identifying the optimum cutting parameters during turning of Ti-6Al-4V. Hence in this paper, Response Surface Model and Fuzzy Logic model has been used to estimate and optimize cutting conditions for cutting force during turning ofTi-6Al-4Vunder Minimum Quantity Lubricant condition. From the observations of these two approaches we can conclude that Response Surface Model and Fuzzy Logic model can be effectively used for identifying the optimum cutting parameters and preventing time consuming experiments.",
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Prediction of cutting force in turning of ti-6al-4v under minimum quantity lubrication (Mql) using response surface model and fuzzy logic model. / Malagi, Ravindra R.; Chougula, Sanjeevkumar R.; Shetty, Ravira J.

In: International Journal of Mechanical and Production Engineering Research and Development, Vol. 8, No. 6, 01.01.2018, p. 263-274.

Research output: Contribution to journalArticle

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