2013
DOI: 10.9790/1684-0722427
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Optimization of Process Parameters in Turning Operation of AISI-1016 Alloy Steels with CBN Using Taguchi Method And Anova

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Cited by 10 publications
(5 citation statements)
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“…It is found that the parameters combination within the proposed range as detailed previously produced lowest surface roughness of brass alloy. Using these data the optimum surface roughness can be predicted according to the relation: Predicted Mean (Ra) = A1+B1+C3-2*(average mean) [1] Where: A1= Average of (Ra) at the first level of tool inclination angle. B1= Average of (Ra) at the first level of feedrate C3= Average of (Ra) at the third level of spindle speed.…”
Section: Estimation Of Optimum Parameters For Roughness (Ra) For Brassmentioning
confidence: 99%
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“…It is found that the parameters combination within the proposed range as detailed previously produced lowest surface roughness of brass alloy. Using these data the optimum surface roughness can be predicted according to the relation: Predicted Mean (Ra) = A1+B1+C3-2*(average mean) [1] Where: A1= Average of (Ra) at the first level of tool inclination angle. B1= Average of (Ra) at the first level of feedrate C3= Average of (Ra) at the third level of spindle speed.…”
Section: Estimation Of Optimum Parameters For Roughness (Ra) For Brassmentioning
confidence: 99%
“…Surface finish of the machined part is one of the common significant criteria to evaluate the operation quality. The literature review has discovered that many attempts have been done to estimate the optimal cutting conditions in the operation of turning [1]. It is very critical part to evaluate and implement optimal machining parameters combination along with the use of suitable cutting tools.…”
Section: Introductionmentioning
confidence: 99%
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“…The combination of low feed rate and high cutting speed was found favourable for better surface finish. Lavanya et al (2013) optimised the machining parameters in turning of AISI 1016 steel using Taguchi method and ANOVA. The statistical analysis concluded that cutting speed had a greater influence on the surface roughness followed by feed and depth of cut had least influence on surface roughness.…”
Section: Introductionmentioning
confidence: 99%
“…Surface roughness is used as the critical quality indicator for the machined surfaces and it affects the several properties such as wear resistance, fatigue strength, coefficient of friction, lubrication, heat transmission, wear rate and corrosion resistance of the machined parts. [3] From the data collection it has been observed that the increase in cutting speed tends to improve the finish, thus the average surface roughness value decreases. [4] Depth of cut has the greatest effect on surface roughness and that an increase in the depth of cut increases the surface roughness and vice-a-versa.…”
Section: Introductionmentioning
confidence: 99%