## 4 Conclusions  
Achieving a target part shrinkage for injection-molded crystalline polymer usually includes a dilemma for molders due to the uncertainty of crystallinity and process-dependent variations. If the completion of the crystallization process can be assured, then the optimization of molding conditions to obtain good part qualities becomes easier. In this study, we proposed a new methodology to detect the enthalpy change of crystalline polymers by monitoring the melt temperature using an infrared temperature sensor. The end of the crystallization was identified as the time when the minimum cooling rate of the measured temperature curve occurred. We then constructed a model to predict the crystallization completion time based on experiments at various melt and mold temperatures using response surface methodology. The validity of the predicted model was further verified by examining part warpage molded under various cooling times. The warpage variation and distribution demonstrated that when the cooling time is longer than the crystallization time, the part warpage stabilizes and the warpage resulting from incomplete crystalliza \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Group**} & **Melt Temp.** & \begin{tabular}{c} **Packing** \\ **Pressure** \\ **(\({}^{\circ}\)C)** \\ \end{tabular} & \
\begin{tabular}{c} **Packing** \\ **Pressure** \\ **(Bar)** \\ \end{tabular} &
\begin{tabular}{c} **Time** \\ **(S)** \\ \end{tabular} & \(t_{\text{cys.}}\) **(S)** & \(P_{\text{Sarg}}\) **(Bar)** \\ \hline B1 & 210 & 900 & 10 & 22.31 & 307.02 \\ B2 & 210 & 900 & 7 & 21.78 & 280.52 \\ B3 & 210 & 900 & 4 & 21.48 & 150.62 \\ B4 & 210 & 600 & 10 & 21.67 & 191.56 \\ B5 & 210 & 600 & 7 & 21.60 & 170.77 \\ B6 & 210 & 600 & 4 & 23.54 & 119.22 \\ B7 & 210 & 300 & 10 & 22.43 & 79.08 \\ B8 & 210 & 300 & 7 & 22.27 & 69.14 \\ B9 & 210 & 300 & 4 & 22.60 & 58.15 \\ B10 & 230 & 900 & 10 & 23.74 & 342.48 \\ B11 & 230 & 900 & 7 & 23.36 & 261.16 \\ B12 & 230 & 900 & 4 & 24.72 & 119.65 \\ B13 & 230 & 600 & 10 & 23.49 & 203.01 \\ B14 & 230 & 600 & 7 & 23.23 & 152.35 \\ B15 & 230 & 600 & 4 & 24.46 & 99.61 \\ B16 & 230 & 300 & 10 & 24.74 & 78.36 \\ B17 & 230 & 300 & 7 & 24.52 & 68.74 \\ B18 & 230 & 300 & 4 & 25.14 & 50.20 \\ B19 & 250 & 900 & 10 & 25.21 & 336.84 \\ B20 & 250 & 900 & 7 & 24.60 & 210.53 \\ B21 & 250 & 900 & 4 & 27.04 & 108.73 \\ B22 & 250 & 600 & 10 & 24.89 & 199.10 \\ B23 & 250 & 600 & 7 & 25.69 & 136.91 \\ B24 & 250 & 600 & 4 & 27.00 & 77.44 \\ B25 & 250 & 300 & 10 & 25.89 & 82.14 \\ B26 & 250 & 300 & 7 & 26.18 & 65.96 \\ B27 & 250 & 300 & 4 & 27.03 & 46.07 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Measured and calculated results of time-averaged pressure. \begin{table}
\begin{tabular}{c c} \hline \hline
**Equations** & **Coefficients** \\ \hline Linear equation: & R-q & R-q (Adj.) \\ \(S_{V}=1.767-0.00204\times P_{\text{Sarg}}\) & 89.36\% & 89.16\% \\ Quadratic equation: & R-q & R-q (Adj.) \\ \(S_{V}=1.910-0.00415\times P_{\text{Sarg}}+6\times 10^{-4}\times P_{\text{Sarg}}^{ 2}\) & 94.00\% & 93.76\% \\ Cubic equation: & R-q & R-q (Adj.) \\ \(S_{V}=1.901-0.003899\times P_{\text{Sarg}}+4\times 10^{-6}\times P_{\text{Sarg}}^{ 2}+10^{-10}\times P_{\text{Sarg}}^{ 3}\) & 94.00\% & 93.64\% \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Adjusted and non-adjusted coefficients of determination for the three types of functions with different orders. tion is excluded, indicating the appropriateness of the predicted crystallization times. To further improve the part shrinkage, we conducted another set of experiments focusing on the influence of packing pressure and time and the possible associated effects of the melt temperature. Using regression analysis, we used the experimental results to build a prediction model that correlates time-averaged cavity pressure with part shrinkage. The predicted model well fits the experimental data.