# Optimization of Carbon Fiber Reinforced Plastic Curing Parameters for Aerospace Application
## 3 Results and Discussions  
### Analysis of Variance (ANOVA)  
ANOVA was performed at a 95% confidence interval [46] to study the influence of curing parameters on tensile strength, impact toughness, and hardness. ANOVA results, summarized in Tables 3-5, were further used for the development of prediction models  
Figure 5: (**a**) Universal tensile testing machine M/s Hualong, Shanghai, China HLE 300 kN. (**b**) Charpy impact toughness testing machine M/s Time Group Inc., Beijing, China Model No. JBS300. (**c**) Rockwell hardness testing machine M/s Time Group Inc., Beijing, China Model No. TH300 used for mechanical testing. Figure 6: Test coupons for (**a**) tensile strength testing, (**b**) impact toughness test, (**b**,**c**) Rockwell hardness test. and optimization. Prediction models for individual responses were developed using the backward elimination method (\(\alpha\) = 0.1). F-value shows the most contributory curing parameters towards the response variable. A \(p\)-value less than 0.05 shows the statistical significance of curing parameters on the response variable. The results showed that the individual factors \(T_{c}\), \(t_{c}\), and \(P_{au}\), and their interaction (\(T_{c}\)\(t_{c}\)) and (\(T_{c}\)\(P_{au}\)), have a significant effect on tensile strength. For impact toughness, all main effects, as well two- and three-way interactions, were found significant, except (\(t_{c}\)\(P_{au}\)). For hardness, only the main effect of \(T_{c}\), \(t_{c}\), and \(P_{au}\) had a significant effect. The \(T_{c}\), \(t_{c}\), and \(P_{au}\) has also been indicated as significant curing parameters in the literature [20; 22; 27; 36; 44]. \begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Source** & **DF** & **Adj SS** & **Adj MS** & **F-Value** & \(p\)**-Value** \\ \hline Model & 7 & 722.798 & 103.257 & 304.35 & 0.000 \\ Linear & 3 & 669.428 & 223.143 & 657.72 & 0.000 \\ \(T_{c}\) & 1 & 135.233 & 135.233 & 398.60 & 0.000 \\ \(t_{c}\) & 1 & 526.500 & 526.500 & 1551.88 & 0.000 \\ \(P_{au}\) & 1 & 7.695 & 7.695 & 22.68 & 0.000 \\ \(2\)-Way inter & 3 & 44.813 & 14.938 & 44.03 & 0.000 \\ \(T_{c}\times t_{c}\) & 1 & 38.837 & 38.837 & 114.47 & 0.000 \\ \(T_{c}\times P_{au}\) & 1 & 5.812 & 5.812 & 17.13 & 0.001 \\ \(t_{c}\times P_{au}\) & 1 & 0.165 & 0.165 & 0.49 & 0.496 \\ \(3\)-Way inter & 1 & 8.556 & 8.556 & 25.22 & 0.000 \\ \(T_{c}\times t_{c}\times P_{au}\) & 1 & 8.556 & 8.556 & 25.22 & 0.000 \\ Error & 16 & 5.428 & 0.339 & & \\ \hline Total & 23 & 728.226 & & & \\ \hline \hline
**R-sq = 99\%, R-sq(adj) = 99\%, R-sq(pred) = 98\%** & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: ANOVA results for impact strength. It was observed that all main effects and three-way interactions were found significant (\(p\)-value < 0.05) for the impact toughness of the CFRP. \begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Source** & **DF** & **Adj SS** & **Adj MS** & **F-Value** & \(p\)**-Value** \\ \hline Model & 5 & 402,449 & 80,490 & 25.85 & 0.000 \\ Linear & 3 & 339,145 & 113,048 & 36.30 & 0.000 \\ \(T_{c}\) & 1 & 69,346 & 69,346 & 22.27 & 0.000 \\ \(t_{c}\) & 1 & 240,544 & 240,544 & 77.24 & 0.000 \\ \(P_{au}\) & 1 & 29,255 & 29,255 & 9.39 & 0.007 \\ 2-way inter & 2 & 63,304 & 31,652 & 10.16 & 0.001 \\ \(T_{c}\times t_{c}\) & 1 & 47,926 & 47,926 & 15.39 & 0.001 \\ \(T_{c}\times P_{au}\) & 1 & 15,378 & 15,378 & 4.94 & 0.039 \\ \hline Error & 18 & 56,054 & 3114 & & \\ Lack-of-Fit & 2 & 5895 & 2947 & 0.94 & 0.411 \\ Pure Error & 16 & 50,159 & 3135 & & \\ Total & 23 & 458,503 & & & \\ \hline \hline
**R-sq = 88\%, R-sq(adj) = 84\%, R-sq(pred) = 78\%** & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: ANOVA results for tensile strength. The table shows the significance (\(p\)-value < 0.05) of individual factors \(T_{c}\), \(t_{c}\), and \(P_{au}\), and their interaction (\(T_{c}\)\(t_{c}\)) and (\(T_{c}\)\(P_{au}\)) on the property of tensile strength.