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Figure 5.2 Surface roughness measurement The 9 different specimens machined by turning process are further checked for surface roughness in order to evaluate the effect of process parameters over the output response. The measure of surface roughness is conducted using portable stylus- type profilometer, Talysurf (Taylor Hobson, Surtronic 3+ and UK).The Figure 5.2 shows the Profilometer used for measuring surface roughness

Figure 5 2 Surface roughness measurement The 9 different specimens machined by turning process are further checked for surface roughness in order to evaluate the effect of process parameters over the output response. The measure of surface roughness is conducted using portable stylus- type profilometer, Talysurf (Taylor Hobson, Surtronic 3+ and UK).The Figure 5.2 shows the Profilometer used for measuring surface roughness

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Table No. 5.1 Constant Experimental Conditions
Table No. 5.1 Constant Experimental Conditions
Table No. 5.2 Input Parameters and Levels The experimental design matrix prepared using Minitab software as per Lo orthogonal array with coded and uncoded factors are shown in Table No. 5.3
Table No. 5.2 Input Parameters and Levels The experimental design matrix prepared using Minitab software as per Lo orthogonal array with coded and uncoded factors are shown in Table No. 5.3
The Table 6.2 shows the mean values of S/N ratio obtained through Minitab Software and it shows that cutting speed is the predominant factor than other two parameters to obtain better surface finish. From the experimental values of Surface roughness the parameter combination A1B2C2 (1500 m/min, 0.1 mm/rev, 0.4mm) is found to have low surface roughness value. Later to that Signal to Noise Ratio plot is obtained by considering smaller is better method and itis observed that the parameter combination A3B1C1 (2000m/min, 0.05 mm/rev, 0.2 mm) provides lesser value for surface roughness measurement. A confirmation experiment is conducted from the obtained setting and ithas shown low surface roughness value comparing to the values obtained through experimental work.
The Table 6.2 shows the mean values of S/N ratio obtained through Minitab Software and it shows that cutting speed is the predominant factor than other two parameters to obtain better surface finish. From the experimental values of Surface roughness the parameter combination A1B2C2 (1500 m/min, 0.1 mm/rev, 0.4mm) is found to have low surface roughness value. Later to that Signal to Noise Ratio plot is obtained by considering smaller is better method and itis observed that the parameter combination A3B1C1 (2000m/min, 0.05 mm/rev, 0.2 mm) provides lesser value for surface roughness measurement. A confirmation experiment is conducted from the obtained setting and ithas shown low surface roughness value comparing to the values obtained through experimental work.
The regression analysis is carried out to check the results obtained from ANOVA. Both ANOVA and Regression analysis performs p-test and it considers the p-test results with values less than 0.05 is found to be the significant one which influences the output response. The regression analysis provides an equation to calculate surface roughness theoretically. The table 6.4 shows the regression results of surface roughness.
The regression analysis is carried out to check the results obtained from ANOVA. Both ANOVA and Regression analysis performs p-test and it considers the p-test results with values less than 0.05 is found to be the significant one which influences the output response. The regression analysis provides an equation to calculate surface roughness theoretically. The table 6.4 shows the regression results of surface roughness.
Related topics:
Mechanical EngineeringMaterials ScienceOrthogonal ArrayOrthogonal Array (oa)
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