is varied. According to Cakir et al. 2009, an increasing cutting speed, the surface roughness will be decreases.
4.7 PURTUBATION PLOT
From the figure 4.8, the cutting parameter consists of actual factors which are cutting speed A, feed rate B and width of cut c. From the graph, an increase in factor A
will reduced the surface roughness. further increase of factor A beyond the experimental range will further reduce the surface roughness until a certain point
where the surface roughness will keep constant where another factor such as tool wear or chip formation will affect the surface roughness. For factor B, the surface tends to
be rougher when the feed rate is higher. In high speed machining of milling, basically the feed rate is set to lowest in producing a smooth surface. This scenario occurs when
the number of passes during machining process will increase when the feed rate is slow. The width of cut that represent the factor C can be consider not significant in the
experiment. From this graph, the maximum value for width of cut will affect the surface roughness but it is not very significant. In a nut shell, the most factors that
affecting the surface roughness is a cutting speed followed and followed by feed rate.
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Figure 4.8: Perturbation plots for experiment
4.8 OPTIMIZATION MACHINING PARAMETER USING RSM
An optimization is a process to determine the best of each cutting parameters to produce the best surface roughness. The optimum parameter obtained from the
analysis will be used in the next machining and the surface roughness from the experiment used to compare with the actual result obtained from the mathematical
model. There are 30 solution proposed by the design expert and the solution is filtered by limiting the range of surface roughness. Then, the best cutting parameter will be
selected for used in machining operation. The criteria for each parameter are shown in table 4.4. The chosen criteria are selected based on the allowable range of parameters
chosen for the experiment. The criteria of the response need to be align with the objective of the experiment which is to minimize the surface roughness. There are two
set of parameters that will be used in the next experiment that are optimized and random parameters. The optimized parameter is determined by using the design expert
and the random parameter is selected based on the allowable range of parameter.
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Table 4.4: Optimization Parameter
Factors Criteria
Minimum Maximum optimized
random
Cutting speed, Vc mmin
In range 100
150 150
150
Feed rate, fz mmtooth In range
0.1 0.2
0.1 0.20
Width of cut, ae mm In range
2 8
8 8
Surface roughness, Ra µm
minimize 0.187
0.186 0.346
The surface roughness values shown in table 4.5 are obtained by using the generated mathematical model. The experimental result of surface roughness obtain during
machining should be close to actual surface roughness value obtain from the mathematical model and differences between experimental result and the actual result
should be lower than 10. The errors selected are to improve the reliability of mathematical model.
Table 4.5: Estimated set of optimized parameters
Numbe r
cutting speed
feed rate
width of cut
Ra Desirabilit
y 1
150 0.1
8 0.18619
5 0.004306
Selecte d
2 150
0.1 7.96
0.18644 1
0.002992
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Figure 4.9: the surface roughness can be obtained from the combination of parameter in no 1
The figure 4.9 shows the combination of each parameter range to produce the optimum surface roughness. The parameter range is set based on the chosen experimental range.
The combination of cutting speed Vc 150 mmin, feed rate fz 0.1mmmin and width of cut ae 8mm will produce the approximate surface roughness, Ra value of 0.186 µm.
4.9 Validation of optimization model
