Optimization of PET Glycolysis Process by Response Surface Methodological Approach: A Two-Component Modelling Using Glycolysis Time and Temperature
Table 3
(a) Summary of results in analyzing lack of fit (LOF) for hydroxyl and acid value. (b) Summary of results in analyzing lack of fit (LOF) for number average molecular weight and glycolysis conversion percentage.
(a)
ANOVA for response surface quadratic model (hydroxyl value)
Source
Sum of squares
DF
Mean square
value
Model
95.57
5
19.11
8.96
<0.0001
Residual
14.93
7
2.13
Lack of fit
7.63
3
2.54
1.19
Pure error
7.30
4
1.82
ANOVA for response surface quadratic model (acid value)
Model
17.97
5
3.59
38.52
<0.0001
Residual
0.65
7
0.093
Lack of fit
0.65
3
0.22
2.365
Pure error
0.000
4
0.000
(b)
ANOVA for response surface quadratic model ()
Source
Sum of squares
DF
Mean square
value
Model
6.627
5
1.325
8.04
<0.0001
Residual
1.153
7
16476.43
Lack of fit
1.153
3
38445.01
2.33
Pure error
0.000
4
0.000
ANOVA for response surface quadratic model (glycolysis conversion percentage)
