Prediction of surface roughness using cutting parameters and vibration signals in minimum quantity coolant assisted turning of Ti-6Al-4V alloy

Vikas Upadhyay, P.K. Jain and N.K. Mehta

International Journal of Manufacturing Technology and Management, 2013, vol. 27, issue 1/2/3, 33-46

Abstract: In this work, an attempt has been made to investigate the role of vibration signals in prediction of surface roughness in minimum quantity coolant assisted turning of Ti-6Al-4V alloy. Initially, a model of surface roughness as a function of cutting parameters was developed to serve as the reference data. Subsequently, two more models were developed - one representing the variation of surface roughness with the vibration and the other represents the variation of surface roughness as a function of cutting parameters and vibration signal considered in tandem. A comparison of the three models established that the model based on simultaneous consideration of cutting parameters and vibration was the most accurate of the three.

Keywords: surface roughness; vibration signals; multiple regression; green manufacturing; sustainable manufacturing; minimum quantity coolant; turning; titanium alloys; surface quality; cutting parameters. (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (4)

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