63。22 <0。0001
A 0。0026 1 0。0026 127。80 <0。0001
D 0。0010 1 0。0010 51。08 <0。0001
AD 0。0002 1 0。0002 10。79 0。0054
Residual 0。0003 14 0。00002
Total 0。0042 17
Table 4d
ANOVA results of dyexp。
lected as a desirability function form for minimizing the warpage distortion and the mass loss。 Furthermore, these inpidual desir- ability functions are can be calculated from Eq。 (1) as a combined desirability function。 More details can be found in the Myers’s and Montgomery book (Myers & Montgomery, 2002)。
5。1。 ANOVA results
The analysis of variance (ANOVA) is conducted and the results of simulation and experimental are shown in Tables 4a–4c and 4d, respectively。 A ‘‘Model F value” is calculated from a model mean square pided by a residual mean square。 It is a test of com- paring a model variance with a residual variance。 If the variances are close to the same, the ratio will be close to one and it is less likely that any of the factors have a significant effect on the re- sponse。 As for a ‘‘Model P value”, if the ‘‘Model P value” is very small (less than 0。05) then the terms in the model have a signifi- cant effect on the response (Myers & Montgomery, 2002)。 Simi- larly, an ‘‘F value” on any inpidual factor terms is calculated from a term mean square pided by a residual mean square。 It is a test that compares a term variance with a residual variance。 If the variances are close to the same, the ratio will be close to one and it is less likely that the term has a significant effect on the re- sponse。 Furthermore, if a ‘‘P value” of any model terms is very small (less than 0。05), the inpidual terms in the model have a sig- nificant effect on the response。
5。1。1。 ANOVA results for simulation
Table 4a lists the ANOVA result of the dxsim。 A ‘‘Model F value” of 3246。14 with a ‘‘Model P value” of less than 0。0001 suggested that the selected model is significant。 A ‘‘P value” for the model term ‘‘A” (the melt temperature) and ‘‘D” (the packing pressure) are less than 0。0001, which are less than 0。05, indicating that the model term ‘‘A” and ‘‘D” are significant。 Additionally, two interac- tion terms, ‘‘AC”, and ‘‘CD”, also have significant influences to the dxsim, namely, through ANOVA, the significant terms that have sig- nificant impacts on the injection molding process can be identified。 Table 4b shows the ANOVA result of the dysim。 A ‘‘Model F value” of
171。94 with a ‘‘Model P value” of less than 0。0001 implies that the
selected model is significant。 A ‘‘P value” for the model term ‘‘A” (the melt temperature) is less than 0。0001, which is less than 0。05, indicating that the model term ‘‘A” is significant。 Similarly, the model term ‘‘C” and ‘‘D” (the inject speed and the packing pres- sure, respectively) are significant。 Additionally, a interaction terms ‘‘AD”, also have significant influences to the dysim。 薄壁塑料件注塑工艺参数英文文献和中文翻译(8):http://www.youerw.com/fanyi/lunwen_82732.html