Wear Behavior of Duplex Stainless Steels Sintered …
227
Table 5 Response table
Level
Load
Material
Condition
Atmosphere
1
29.19
26.58
26.6
27.51
2
27.67
30.28
30.26
29.35
Delta
1.52
3.7
3.66
1.84
Rank
4
1
2
3
table is based on delta statistics comparing the relative impact magnitude. The delta
value for each element is the largest minus the least average. Depending on delta
values, ranks are allocated; rank 1 at the highest value, rank 2 at the next higher
value, etc. The rank reveals the importance of the individual response to each factor.
The response table shows the material is the main cause influencing the wear rate of
DSS closely followed by condition. ANOVA table shows that there is no significant
contribution by load and atmosphere. This is because of the very less delta value,
which shows that the change of levels does not affect the wear rate.
3.2 Selection of Optimum Levels
The response Table 5 shows the average feature of each response for each variable
level. The rank indicates the relative importance of the response of each factor.
The rank and delta value shows that the main parameters influencing the wear rate
followed by load and atmosphere are material and condition. To assess the effect
of system variables on the measurement of wear rates ANOVA was performed.
Table 6 shows the S/N data for wear rate values. ANOVA table reveals that material
has influenced 18% towards wear rate compared to other factors such as load and
atmosphere. Figure 1 shows the Response Graphs for Wear Rate. The response graph
shows that forged DSS under partial vacuum in 20 N is the optimized one. The
response graph also reveals that, wear rate increases with an increase in load. From
the interaction plot, it is noticed that there is no factor interaction among each other
influencing the wear rate of DSS.
3.3 Confirmation Experiment
Confirmation experiments were conducted. The optimum process parameters
for wear rate and their predicted and experimental values are given. The
optimum predicted value is 0.0133 mm
3 /mm, whereas the experimental value is
0.0140 mm
3 /mm. The error is 5%, so the optimization technique holds good for
Wear Rate.
227
Table 5 Response table
Level
Load
Material
Condition
Atmosphere
1
29.19
26.58
26.6
27.51
2
27.67
30.28
30.26
29.35
Delta
1.52
3.7
3.66
1.84
Rank
4
1
2
3
table is based on delta statistics comparing the relative impact magnitude. The delta
value for each element is the largest minus the least average. Depending on delta
values, ranks are allocated; rank 1 at the highest value, rank 2 at the next higher
value, etc. The rank reveals the importance of the individual response to each factor.
The response table shows the material is the main cause influencing the wear rate of
DSS closely followed by condition. ANOVA table shows that there is no significant
contribution by load and atmosphere. This is because of the very less delta value,
which shows that the change of levels does not affect the wear rate.
3.2 Selection of Optimum Levels
The response Table 5 shows the average feature of each response for each variable
level. The rank indicates the relative importance of the response of each factor.
The rank and delta value shows that the main parameters influencing the wear rate
followed by load and atmosphere are material and condition. To assess the effect
of system variables on the measurement of wear rates ANOVA was performed.
Table 6 shows the S/N data for wear rate values. ANOVA table reveals that material
has influenced 18% towards wear rate compared to other factors such as load and
atmosphere. Figure 1 shows the Response Graphs for Wear Rate. The response graph
shows that forged DSS under partial vacuum in 20 N is the optimized one. The
response graph also reveals that, wear rate increases with an increase in load. From
the interaction plot, it is noticed that there is no factor interaction among each other
influencing the wear rate of DSS.
3.3 Confirmation Experiment
Confirmation experiments were conducted. The optimum process parameters
for wear rate and their predicted and experimental values are given. The
optimum predicted value is 0.0133 mm
3 /mm, whereas the experimental value is
0.0140 mm
3 /mm. The error is 5%, so the optimization technique holds good for
Wear Rate.