Figure 1 shows a 3D model of an automotive tailgate handle. Surfaces A and B are appearance surfaces, and must not have defects such as gate residue, weld lines, air pockets, or insufficient filling. Surfaces C, D, and E are assembly surfaces. Customer requires the total warpage deformation of plastic part to be controlled within 0.5 mm. Dimensions of plastic part are 256.4 mm * 59.91 mm * 84.63 mm, the thinnest wall thickness is 0.5 mm, the thickest wall thickness is 6 mm, average wall thickness is 3.5 mm, and weight is 130.2 g.

 

Figure 1 Automotive Tailgate Handle Model

NX analysis shows poor surface continuity of plastic part. After importing model into CAD Doctor in STEP format, several geometric defects were detected. After automatic repair (tolerance 0.0254 mm) and simplification of fillets and chamfers, final product was imported into MoldFlow in UDM format for analysis. Due to short delivery time required for plastic part and long analysis cycle using 3D methods, considering manufacturing costs and mold delivery time, a Dual Domain mesh type was used to mesh car tailgate handle, with a global edge length of 2 mm. Mesh repaired result is shown in Figure 2. There are 53,986 mesh elements, with a maximum aspect ratio of 6 mm, a minimum of 1.16 mm, and an average of 1.67 mm. Mesh matching percentage is 91.2%, and mutual percentage is 88.2%, indicating good mesh quality that meets requirements for subsequent injection molding process analysis.

 

Figure 2: Mesh Generation Results
Gate location is inextricably linked to molding quality of plastic part. Warpage of molded part can be optimized by designing a reasonable gate location, and even weld lines can be avoided. Guo Xu et al. studied gate location of injection molds for separator tanks based on Moldflow. By comparing results of flow front temperature analysis and weld line location analysis, they concluded that the closer gate location is to central axis of plastic part, the fewer molding defects there will be. Gate location analysis using Moldflow software is shown in Figure 3. Analysis shows that surface D of plastic part is point of minimum flow resistance of plastic melt and point of highest gate matching degree. Therefore, gate location is determined to be at node N564 497.

 

Figure 3: Gate Location Analysis Results

Based on experience, an initial scheme is designed. First, flow front temperature and warpage deformation are checked for reasonableness. Then, molding process scheme is evaluated to provide a basis for subsequent optimization. Initial design of automotive tailgate handle gating system is shown in Figure 4. Main runner is 188 mm long, with an upper diameter of φ3.5 mm and a lower diameter of φ8 mm, and is set as a hot runner. Primary runner has a trapezoidal cross-section, with an upper length of 10 mm, a lower length of 8.6 mm, a height of 8 mm, and a total length of 260 mm, and is set as a standard runner. Secondary runner has a circular cross-section, with an upper diameter of φ8 mm and a lower diameter of φ6 mm, and is also set as a standard runner. Submarine gate also has a circular cross-section, with an upper diameter of φ6 mm and a lower diameter of φ3 mm, and is also set as a standard runner. After gating system is created, "fill + hold pressure + warpage" analysis sequence is used, and injection process parameters are set as follows: melt temperature 265 ℃, mold surface temperature 90 ℃, pressure during V/P switching 130 MPa, and other parameters are set to default. Flow front temperature analysis results are shown in Figure 5. Flow front temperature ranges from 185 to 267.8 ℃, with a temperature difference of 82.8 ℃. A smaller flow front temperature difference indicates better molded part quality.

 

Figure 4: Initial design of gating system

 

Figure 5: Flow front temperature analysis results
Due to assembly requirements between plastic part and other automotive parts, glue cannot be added to rib areas. Flow front temperature was optimized by increasing number of gates and changing process parameters, as shown in Figure 6.

 

Figure 6: Changes in gate location and data results

Experiment selected seven factors as research objects: mold temperature (A), melt temperature (B), injection time (C), V/P switching pressure (D), holding time (E), holding pressure (F), and cooling time (G). Based on feasible process range determined by CAE analysis, a 7-factor, 3-level orthogonal array was used for the experimental design. Level values for each factor are shown in Table 1.
Simulation experiments were conducted using Moldflow software on 7 factors at 3 levels shown in Table 1. Maximum warpage deformation and flow front temperature difference were used as evaluation indicators. A total of 18 experiments were completed, and results are shown in Table 2. Further range analysis was performed on experimental data, yielding analysis results shown in Tables 3 and 4.

 

Table 1: Values of 7 Factors at 3 Levels

 

Table 2: Orthogonal Experiment Results

 

Table 3: Range Analysis of Maximum Warpage Deformation

 

Table 4: Range Analysis of Flow Front Temperature Difference

 

Table 5: Response Surface Experiment Design and Results
From Tables 3 and 4, it can be seen that factors affecting maximum warpage deformation are in the order of E>F>A>D>C>G>B; factors affecting flow front temperature difference are in the order of C>E>G>D>F>B>A. Based on multi-index comprehensive balance method analysis, process parameters were optimized by systematically evaluating interaction effects of experimental data. Quality characteristic indicators were prioritized, key control elements were determined through main effect analysis and range analysis. Based on multi-attribute decision theory, a parameter configuration optimization scheme was established, and A₂B₂C₁D₁E₃F₃G₂ was ultimately determined as optimal parameter combination satisfying multi-objective constraints.

Based on orthogonal experimental results, effects of each factor on maximum warpage and temperature difference at flow front were preliminarily determined. Factors A, E, F, and G were selected as main design objects, while factors B, C, and D were determined using comprehensive balance method. A response surface design was established using Design Expert. Experimental factors were: mold temperature (A), holding time (E), holding pressure (F), and cooling time (G), with maximum warpage deformation as main indicator. Each factor was tested at two levels, maximum and minimum, for a total of 27 sets of experiments. There were 24 factorial points and 3 center points. Response surface design is shown in Table 5.
Model fitting summary is shown in Figure 7. As shown in Figure 7, recommended model for maximum warpage deformation analysis is quadratic model. This model has good modeling ability for complex response relationships, especially suitable for nonlinear effects, providing high-confidence data-driven support for multi-objective optimization system of process parameters and innovative design of plastic parts within integrated learning framework. Figure 8 shows model diagram.

 

Figure 7: Model Fitting Summary

 

Figure 8: Model Diagram
In optimization module, optimal parameters are generated by setting minimum warpage deformation value, as shown in Figure 9. Desirability of maximum warpage deformation is 1, indicating a high degree of matching. When mold temperature is 90 ℃, holding time is 27.0778 s, holding pressure is 114.8156 MPa, and cooling time is 19.5186 s, minimum warpage deformation is 0.280117 mm.

 

Figure 9. Response Surface Prediction

Optimal parameters were obtained through response surface analysis. Injection molding process parameters were constructed using Moldflow software: mold temperature 90 ℃, melt temperature 277 ℃, injection time 0.5 s, pressure during V/P switching 120 MPa, holding time 27.0778 s, holding pressure 114.8156 MPa, and cooling time 19.5186 s. Based on orthogonal experimental results, optimal parameter combination was obtained through a comprehensive balance method, then optimal process parameters were derived through response surface analysis.

Uneven shrinkage is main cause of warpage deformation in plastic parts. Anisotropic shrinkage is mainly manifested in the fact that shrinkage rate in thickness direction is significantly higher than that in the flat area during melt molding, leading to increased warpage deformation. Therefore, multi-stage holding pressure and attenuation holding pressure schemes can effectively reduce warpage deformation. Results of freezing layer factor are shown in Figure 10. As shown in Figure 10(a), melt at gate solidifies at 16.21 s, hindering transmission of holding pressure. Since original holding time was 26.2931 s, holding pressure continued for a period during melt solidification, which could cause over-holding in molded part, leading to defects such as flash, warping, dimensional errors, shrinkage marks, flow marks, or uneven gloss. Therefore, final holding time was set to 17 s, and holding pressure was increased at locations where warping deformation was more severe. As shown in Figure 10(b), cooling time of two wings of molded part is approximately 8.208 s. Therefore, a holding time of 9 s was set, with a holding pressure of 132 MPa. Removing holding pressure after melt at gate solidifies allows for better pressure-holding and shrinkage compensation, shortens injection molding cycle, improves production efficiency. Figure 11 shows results before and after warpage optimization. Through optimization, warpage decreased from 0.2935 mm to 0.1743 mm, meeting assembly requirements of plastic part.

 

Figure 10: Freeze-in-place factor results

 

Figure 11: Results before and after warpage optimization

Weldlines mainly occur at orifice on surface C and assembly stud on surface E. This can be addressed by changing gate location, increasing melt temperature, and enhancing venting. Figure 12 shows results of weldline location optimization. Increasing number of gates caused melt to collide at surface B of plastic part to be molded, resulting in a relatively obvious weldline. Because plastic part is black, weldline is not easily detected under light reflection. After communicating with customer, it was agreed that weldline would remain. Weldlines on surfaces C and E can be avoided by venting excess air through insert fitting gap.

 

Figure 12 Analysis Results of Weld Line Location Optimization

Cavitation is mainly distributed at two wings of surface A, opening of surface C, assembly studs and ribs of surface E. Design of venting grooves should be enhanced at these corresponding locations. Results of venting location optimization analysis are shown in Figure 13. Venting has not been effectively improved. Therefore, mold flow analysis results will be transmitted to mold designer to enhance design of venting grooves at reasonable locations on surface A. Venting at opening of surface C and assembly studs on surface E can be achieved through assembly gaps between slider and inserts and other mold parts. Ribs on surface E are at the furthest point of flow front and have a deep molding depth, making them prone to defects such as insufficient filling and burning. Therefore, insert venting should be designed at this location, as shown in Figure 14.

 

Figure 13 Analysis Results of Cavitation Location Optimization

 

Figure 14 Mold Venting Design