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Injection molding is a widely used polymer manufacturing process, and integrating sustainability is essential. As material testing demand increases, efficient methods for producing multiple samples are crucial. Family molds enable multiple sample production in a single cycle but pose challenges in achieving balanced flow, leading to sink marks and shrinkage that affect test accuracy. This study addresses these issues by analyzing sink marks, shrinkage, and their variance among specimens. A Grey-based Taguchi method systematically evaluates the effects of injection speed, melt temperature, injection pressure, holding pressure, holding time, and cooling time. Optimal conditions were determined as 40 mm/s injection speed, 170°C melt temperature, 110 MPa injection pressure, 35 MPa holding pressure, and a 7-s holding time. ANOVA results indicate that melt temperature, holding time, and holding pressure significantly influence sink marks and shrinkage. Under optimal conditions, the GRD value improved from 0.638 to 0.643. Furthermore, material testing confirmed the reliability of the optimized specimens, with tensile and flexural strengths within a 5% error margin of datasheet values. These findings validate the effectiveness of the proposed method in enhancing sample quality and consistency in family mold injection molding.

In the realm of injection-molded parts, small length scale deformation defects such as sink marks often pose a major challenge to the aesthetics or functionality of the parts. To address this problem, we present a comprehensive thermoelastomechanical approach that calculates the deformation of injection molded plastic by solving the elastic problem at each time step. In our methodology, two treatments of the molten core are considered: one as a liquid and the other as a rubbery state. Our results suggest that the rubbery state treatment provides higher accuracy in predicting the deformation results, as it maintains the displacement of the localized thermal shrinkage in its vicinity. The validity of our method is supported by empirical measurements on produced parts from the existing literature as well as on samples that we molded independently.

The sink mark is one common defect of the injection-molded thermoplastics, which is harmful to the part appearance. A procedure for the sink mark prediction was proposed to build the finite element method (FEM) model in Abaqus. The temperature and pressure distributions were imported as boundary conditions at a different time from the injection molding simulation software Moldflow. The user subroutines UEXPAN and UMAT were coded and implemented in Abaqus to describe the pressure-volume-temperature (PVT) behaviors under actual cooling conditions and the polymer constitutive relationship. The PVT curves of the thermoplastic were obtained by the piston-die method at a cooling rate of 5  ° C/min. The crystallizing behaviors were measured by a differential scanning calorimetry and adapted to modify the PVT curves at different cooling rates. The tension-compression tests at different temperatures were performed to obtain the stress-strain curves. The simulation of injection molding was conducted in the software Moldflow. The deflection tests were conducted on the coordinate measuring machine (CMM) to validate the predicted sink mark. It was found that the subroutines of UEXPAN described the volume variations under different cooling rates successfully. Furthermore, the subroutine UMAT predicted stress-strain curves successfully at different temperatures and strain rates. The predicted sink mark in Abaqus agreed well with the measured one. The sink mark depth from Abaqus reached one third of the experimental one and had obvious improvement than that from Moldflow.

This paper deals with minimization of sink marks occurring behind the rib in plastic injection molding. In terms of rib structure and injection processing parameters, a theoretical analysis model was created. Meanwhile, finite element flow analysis with design of experiments (DOE) and genetic algorithm (GA) was integrated. Values of sink mark depth depend on design variables and technological parameters. Out of all, the four most influential variables, viz., rib thickness, mold temperature, melt temperature, and coolant temperature, were selected for optimization. The mathematic relation between sink mark depth and variables was established by conducting a set of FE analyses at various combinations of variables based on central composite design (CCD). Furthermore, the influence incidence of each factor and interaction between each variable on sink marks were investigated. The prediction model of sink marks was effectively coupled with GA for optimization of variables to minimize the sink depth. Results of the contrast analysis indicated that the proposed methodology could be used effectively in minimizing sink mark depth and parameter optimization design.

This paper addresses the challenges encountered during the injection molding process to ensure high-quality production of parts. The main problem to deal with in the study is achieving uniform filling, effective cooling, and minimizing defects such as air traps, weld lines, and sink marks. Through the use of virtual simulations, the research identifies optimal working parameters and analyzes the behaviour of the material and mold during the injection process. The simulations validate that the proposed settings can achieve even filling with-out defects and efficient cooling, ensuring the part remains in a solid state upon ejection. The study also explores strategies to address potential issues, such as implementing ventilation systems for air traps and optimizing cooling channels for better heat dissipation. The findings demonstrate that virtual simulations are an effective method for optimizing the injection molding process, leading to high-quality, defect-free products. The analysis also highlights the importance of gate configuration, noting that fewer than four gates can significantly increase the risk of short shot defects. Overall, this research contributes valuable insights into the injection molding process, enhancing the understanding of how to achieve high-quality artificial ski slope tiles while minimizing manufacturing defects.

This paper deals with minimization of sink depths in injection-molded thermoplastic components by integrating finite element (FE) flow analysis with central composite design (CCD) of experiments and genetic algorithm (GA). Sink-mark depth depends on various process and design variables. Out of all, four most influential variables viz. melt temperature, mold temperature, pack pressure, and rib-to-wall ratio were used for optimization. A set of FE analyses were conducted at various combinations of variables based on the CCD array. A second-order-response surface regression model (RSRM) was developed based on the CCD. The second-order model was effectively coupled with GA for optimization of variables to minimize the sink depth. Results are encouraging and the proposed methodology could be used effectively in minimizing sink-mark depths.

Multi-pass single-point incremental forming achieves large-angle part processing through multiple forming, and as the number of forming times increases, the number of forming defects on the workpiece also increases, significantly affecting the forming quality of the workpiece. This study focuses on multi-pass single-point incremental forming defects, investigating the effects of machining paths and different variable parameters on forming defects. It comprehensively analyses the effects of axial and radial compensation machining paths on forming defects through simulations and experiments. The results show that the greater the axial compensation, the more severe the wall thickness reduction and the fewer the sink mark defects. After radial compensation, the minimum wall thickness of the formed parts is reduced, and the larger the radial compensation, the more obvious the sink mark defects. The effects of variable pass angle, tool diameter, and layer feed rate on forming defects were also investigated. The results show that a decrease in the angle between passes reduces the minimum wall thickness of the workpiece. Furthermore, gradually increasing the tool diameter and decreasing the feed rate can increase the wall thickness of the workpiece; gradually decreasing the angle between passes increases the number of sink defects, whereas gradually increasing the tool diameter can reduce the number of sink defects. The sink defect is the smallest with the same layer feed rate. The effectiveness and accuracy of the simulation results have been verified through experiments, and this is of great significance for improving the forming accuracy of workpieces.

This study investigates the challenges and potential of conventional injection molding for producing thick-walled optical components. The research primarily focuses on optimizing process parameters and mold design to enhance product quality. The methods include software simulations and experimental validation using polycarbonate test samples (optical lenses). Significant parameters such as melt temperature, mold temperature, injection pressure, and packing pressure were varied to assess their impact on geometric accuracy and visual properties. The results show that lower melt temperatures and higher mold temperatures significantly reduce the occurrence of dimensional defects. Additionally, the design of the gate system was found to be crucial in minimizing defects and ensuring uniform material flow. Effective packing pressure was essential in reducing volumetric shrinkage and sink marks. Furthermore, we monitored the deviation between the predicted and actual defects relative to the thickness of the sample wall. After optimization, the occurrence of obvious defects was eliminated across all sample thicknesses (lenses), and the impact of the critical defect, the sink mark on the planar side of the lens, was minimized. These findings demonstrate the substantial potential of conventional injection molding to produce high-quality thick-walled parts when these parameters are precisely controlled. This study provides valuable insights for the efficient design and manufacturing of optical components, addressing the growing demand for high-performance thick-walled plastic products.

Conventional injection molding is widely used to produce plastic parts, mainly in the automotive industry, due to the high production ratios and quality of injection parts. Low mold temperatures are usually employed to decrease cycle molding time and final process costs; however, resulting surface defects include weld lines, sink marks, and warpage. Therefore, plastic parts are often subjected to secondary processes to reduce the surface defects. A dynamic mold heating and cooling control technology, rapid heat cycle molding (RHCM), was employed to optimize the injection molding process. The present study combined convection heating (pressurized water flow) and external infrared heating systems to investigate the effect of dynamic temperature control on the injection molding process. The infrared heating system was custom built to allow studying under controlled conditions the influence of several process parameters on the resulting morphology and mechanical properties. Results show significant gains from using the RHCM technology to optimize the conventional process, namely, at 100 °C no frozen layer is formed while simultaneously increasing the Young’s modulus. Industrial companies struggling with defects resulting from the thermal changes during injection molding can thus consider RHCM as a mitigation strategy and use these results as a guide for tool design and implementation of the technique.

The process of plastic injection is one of the plastics forming processes is mostly done. Problems are often experienced in the injection process is the occurrence of product defects in the finished goods so that they can slow down the production process. This study aims to analyze the effect of injection temperature on product defects that occurred. Product as the object of the research is a standing hanger for wardrobe. Products are printed by using polypropylene material. Injection process uses injection molding manual toggle system. Injection temperature varied based on the melting temperature, namely 155, 160, 165, and 170°C. The results showed the low injection temperature of 155°C, defective products occur more dominant than the injection temperature of 160°C and 165°C and mold filled at an injection temperature of 170°C. Injection temperature under the melting temperature will result in a more dominant defect occurs. By raising the temperature above the melting temperature injection can reduce the occurrence of product defects. The defects that occur in the process of injection plastic products buffer hanger hangers for cabinets are short shot, jetting, flashing, sink marks and shrinkage.