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Estimation of surface roughness using cutting parameters, force, sound, and vibration in turning of Inconel 718

  • Yogesh Deshpande
  • Atul AndhareEmail author
  • Neelesh Kumar Sahu
Technical Paper

Abstract

The present work is aimed at in-process estimation of surface roughness using cutting parameters along with cutting force, sound, and vibration in turning of Inconel 718 with cryogenically treated and untreated carbide inserts. Initially, prediction models are developed by regression analysis using only cutting parameters and then using only force, sound, and vibration. Later on, these models are modified to include all the parameters after performing correlation analysis for determining significant parameters. The modified models are developed using only significant parameters from the cutting parameters and measured responses. The prediction results of modified regression models are compared with experimental results and fine association of fit between measured and estimated surface roughness is confirmed. Based on coefficient of determination (R 2) values, the regression models are found to be better for estimating surface roughness. Finally, it is found that modified regression models are estimating surface roughness with more than 90% accuracy which can be said as acceptable for the two types of inserts used. Use of sound emitted while machining along with values of cutting parameters, force, and vibration to predict surface roughness has not been reported earlier particularly for Inconel 718. As cutting force, sound, and vibration can be measured during the turning process, this method can be useful for real-time control of the process to get the desired surface roughness for machining of difficult to cut material like Inconel 718.

Keywords

Surface roughness Inconel 718 Regression analysis Cryogenic treatment 

Abbreviations

CNC

Computer numerical control

CCD

Central composite design

MRA

Multiple regression analysis

RSM

Response surface methodology

FOEC

First-order equation using cutting parameters

FOER

First-order equation using response parameters

FOEM

Modified first-order equation

PCA

Pearson correlation analysis

List of symbols

v

Cutting speed (m/min)

f

Feed rate (mm/rev)

d

Depth of cut (mm)

Fc

Cutting force (N)

S

Sound pressure level (Pa)

Vv

Vibration velocity (m/s)

n

Number of experiments

\(R_{\text{ai}}\)

Average of measured surface roughness in μm

\(\hat{R}_{\text{ai}}\)

Estimated surface roughness

R2

Coefficient of determination

AE

Absolute error (%)

MAE

Mean absolute error (%)

MSE

Mean square error (%)

Notes

Acknowledgements

This research work was carried out with assistance from the Technical Education Quality Improvement Program, Phase II (TEQIP-II), Visvesvaraya National Institute of Technology, Nagpur, under the Ministry of Human Resource Development (MHRD), Government of India, New Delhi.

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Copyright information

© The Brazilian Society of Mechanical Sciences and Engineering 2017

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringVisvesvaraya National Institute of TechnologyNagpurIndia

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