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In practical applications, polyurethane (PU) foam must be rigid to meet the demands of various industries and provide comfort and protection in everyday life. PU foam components are extensively used in structural foam, thermal insulation, decorative panels, packaging, imitation wood, and floral foam, as well as in models and prototypes. Conventional technology for producing PU foam parts often leads to defects such as deformation, short shots, entrapped air, warpage, flash, micro-bubbles, weld lines, and voids. Therefore, the development of rigid PU foam parts has become a crucial research focus in the industry. This study proposes an innovative manufacturing process for producing rigid PU foam parts using silicone rubber molds (SRMs). The deformation of the silicone rubber mold can be predicted based on its wall thickness, following a trend equation with a correlation coefficient of 0.9951. The volume of the PU foam part can also be predicted by the weight of the PU foaming agent, as indicated by a trend equation with a correlation coefficient of 0.9824. The optimal weight ratio of the foaming agent to water, yielding the highest surface hardness, was found to be 5:1. The surface hardness of the PU foam part can also be predicted based on the weight of the water used, according to a proposed prediction equation with a correlation coefficient of 0.7517. The average surface hardness of the fabricated PU foam part has a Shore O hardness value of approximately 75. Foam parts made with 1.5 g of water added to 15 g of a foaming agent have the fewest internal pores, resulting in the densest interior. PU foam parts exhibit excellent mechanical properties when 3 g of water is added to the PU foaming agent, as evidenced by their surface hardness and compressive strength. Using rigid PU foam parts as a backing material in the proposed method can reduce rapid tool production costs by about 62%. Finally, an innovative manufacturing process for creating large SRMs using rigid PU foam parts as backing material is demonstrated.

Warpage is one of the prominent issues in Fused Filament Fabrication. The cause of this is the rapid cooling of the polymer during extrusion. The residual thermal stresses accumulated within the print part result in a shape distortion and subsequent detachment of the object from the print bed. In this study, both experimental and numerical approaches were used to identify the stresses due to thermal shrinking that occurs in soft polymers such as wax. A temperature sweep test was performed using a rotational rheometer to measure the magnitude of axial forces that are generated due to the thermal shrinking of a thin layer of 3D printable wax. The thermal stresses responsible for warpage were computed analytically and using the FEA. It was found that due to thermal processes, the stress magnitude can reach a value of 1.17 MPa. This value is enough to cause the plastic deformation in the wax part having a thin elongated shape. In addition, Taguchi's robust design has identified two major FFF parameters that impact the warpage in amorphous soft polymers. They are the printing speed and the print bed temperature. To achieve a low level of warpage, it is important to make sure that the layer deposition occurs at medium speeds and the print bed temperature is moderately high according to the findings of this study.

Injection molds are production tools that require detailed analysis based on the quality of the resulting part, the impact on cycle times, and the expected production volume. Cooling channels also play a critical role in mold performance and product quality as they largely determine cycle time. Designs that incorporate conformal cooling channel (CCC) geometries that conform to or align with the part contour are currently being explored as an alternative to conventional cooling channel designs in injection molds. In this study, a simulation of CCC geometries was performed and their effects on mold temperatures and warpage were investigated. Two cross-sectional geometries, circular and square, were selected for a three-factor level design of experiments (DOE) analysis. The response variables used were mold temperatures and part warpage. A cup-shaped part with upper and lower diameters of 54 and 48 mm, respectively, a height of 23 mm and a thickness of 3 mm was used for the injection molded part. A comparison was also made between two materials for the injection mold, steel and polycarbonate. The DOE results showed that the distance between the CCC and the injected part and the diameter or side of the square have significant effects on the response variables for both systems (steel and polycarbonate molds). In addition, a comparison between conventional and conformal cooling channels was analyzed using a cup-shaped part and a less rigid part geometry. The finite element simulation results show a 9.26% reduction in final warpage in the cup-shaped part using CCCs compared with the conventional cooling methods in steel. When using parts with lower geometry stiffness, the use of CCCs reduced final part warpage by 32.4% in metal molds and by 59.8% in polymer molds.

The current work investigates the auxetic tensile deformation behavior of the inversehoneycomb structure with 5 × 5 cells made of biodegradable poly(butylene adipate-coterephthalate) (PBAT). Fused deposition modeling, an additive manufacturing method, was used to produce such specimens. Residual stress (RS) and warpage, more or less, always exist in such specimens due to their layer-by-layer fabrication, i.e., repeated heating and cooling. The RS influences the auxetic deformation behavior, but its measurement is challenging due to its very fine structure. Instead, the finite-element (FE)-based process simulation realized using an ABAQUS plug-in numerically predicts the RS and warpage. The predicted warpage shows a negligibly slight deviation compared to the design topology. This process simulation also provides the temperature evolution of a small-volume material, revealing the effects of local cyclic heating and cooling. The achieved RS serves as the initial condition for the FE model used to investigate the auxetic tensile behavior. With the outcomes from FE calculation without consideration of the RS, the effect of the RS on the deformation behavior is discussed for the global force-displacement curve, the structural Poisson's ratio evolution, the deformed structural status, the stress distribution, and the evolution, where the first three and the warpage are also compared with the experimental results. Furthermore, the FE simulation can easily provide the global stress-strain flow curve with the total stress calculated from the elemental stresses.

The material extrusion additive manufacturing (MEAM) process for polymers seems straightforward. However, several controlled and uncontrolled factors affect the 3D printed product quality, e.g., MEAM process parameters, thermomechanical properties of the material, and part design. Therefore, it is crucial to understand these interlinked factors of part geometry, material properties, and 3D printing (3DP) process parameters to optimize 3D printed product quality. The numerical models and simulation tools can predict the thermomechanical performance of the MEAM process under given input parameters (material, design, and process variables) and reduce the research and development costs significantly. However, the numerical models and tools need further exploration and validation of simulation predictions for their adaptability and reliability. Therefore, in this study, numerical simulations were performed to observe the impact of process parameters on the part quality of MEAM 3D printed components. The two crucial process parameters (i.e., extrusion temperature and layer resolution) were varied while keeping the other process parameters, part geometry (tensile testing coupon), and material properties (acrylonitrile butadiene styrene (ABS)) constant. These two process parameters were sequentially optimized for optimum part quality, first by varying the extrusion temperature and secondly by changing the printing resolution using the optimum printing temperature. The 3DP process quality was evaluated in terms of dimensional accuracy, distortions, and residual stresses. Finally, the specimens were 3D printed under similar process conditions to validate the numerical model predictions.

In fused deposition modelling (FDM) based on the selected raster pattern, the developed internal thermal residual stresses can vary considerably affecting the mechanical properties and leading to distinct part distortions. This phenomenon is more pronounced in semi-crystalline than amorphous polymers due to crystallisation. Hence, this study focuses on the simulation of the FDM process of a semi-crystalline polymer (polypropylene) with raster patterns such as line (90°/90°), line (0°/90°), zigzag (45°/45°), zigzag (45°/-45°), and concentric from Cura (slicing software). The simulation provides visualisation and prediction of the internally developed thermal residual stresses and resulting warpage with printing time and temperature. The sample with a line (90°/90°) raster pattern is considered as the reference sample in order to compare the relative levels of residual stress and warpage in the other printed/simulated samples. Among the considered raster patterns, the concentric pattern displays the lowest amount of warpage (5.5% decrease) along with a significant drop in residual stress of 21%. While the sample with a zigzag (45°/-45°) pattern showed the highest increase of 37% in warpage along with a decrease of 9.8% in residual stresses. The sample with a zigzag (45°/45°) pattern, exhibited a considerable increase of 16.2% in warpage with a significant increase of 31% in residual stresses. Finally, the sample with a line (0°/90°) raster pattern displayed an increase of 24% increase in warpage with an increase of 6.6% in residual stresses.

This paper uses a multi-objective optimization method to optimize the injection-molding defects of automotive pedals. Compared with the traditional automotive pedal material, aluminum alloy, the polymer pedal containing glass fibers not only reduces the aluminum pedal by at least half, but also improves the strength and hardness of the fibers by adjusting the orientation of the fibers in all directions. Injection factors include: filling time, filling pressure, melt temperature, cooling time, injection time, etc. For the optimization process influencing factors, herein, we focus on warpage analyzed via flow simulation, and setting warpage parameters and cycle time as discussed by setting different cooling distributions, pressures and temperature schemes. The multi-objective optimization design was mainly used to describe the relationship between cycle time and warpage, and the Pareto boundary was used for cycle time and warpage to identify the deviation function and radial-basis-function network. We worked with a small DOE for building the surface to run SAO programming-which improved the accuracy of the response surface by adding sampling points-terminating the time when the warpage value met the solution requirements, to find out the global optimal solution of the warpage value under different cooling times. Finally, the results highlighted four influencing parameters that match the experimental image of the actual production.

In this study, we determined the effects of design and processing parameters of precision injection molding (PIM) to minimize warpage phenomena of micro-sized parts using various plastics (polyoxymethylene (POM), acrylonitrile-butadiene-styrene (ABS), polypropylene (PP), polyamide (PA), and ABS+ polycarbonate (PC)). We applied a numerical simulation (Moldflow) to determine the runner's balance in multi-cavities of the micro-sized part and simulate the warpage phenomenon of micro-parts with PIM. We used simulation data to fabricate a steel mold by computer numerical control (CNC) machining. In this, we study manufactured a micro-sized part and measured its warpage value using various PIM process parameters (melt temperature, mold temperature, injection pressure, and filling time). In order to obtain optimal results (i.e., minimum warpage), we employed the Taguchi method and grey theory to discern the influence of each process parameter on PIM. Finally, we determined that the most significant PIM process parameter influencing the warpage phenomenon of micro-sized parts was the mold temperature, regardless of whether in terms of the experimental results, numerical simulations, or grey theory. The PA material had the most suitable properties for application for micro-sized parts, regardless of whether in terms of experimental results, numerical simulations, or grey theory for PIM. This study also illustrates that micro-sized parts can be fabricated by PIM without the use of micro-injection molding, and we determined that the mold temperature required for molding does not need to be higher than the glass-transition temperature of the material.

Many challenges are associated with the injection compression molding process for producing a half-pallet (1320 mm × 1110 mm × 75 mm, length × width × height), which is butt-welded to another one for enhancing its strength. This pooled high-density polyethylene (HDPE) pallet is able to endure the impacts of a heavy load and a low ambient temperature. Reducing the warpage of a half-pallet is, therefore, essential for reducing the residual internal stress within the welded portions. An advanced Moldex3D package helps to detail the temperature distribution and warpage of a half-pallet. The pre-setting molding parameters from a mass-production factory produce half-pallets with worse flatness. In this investigation on using appropriate cooling water temperatures within the core and cavity plates of the mold, the numerical results show that the warpage of the top surface of the half-pallet was 11.549 mm, low warpage with respect to this large-scale pallet. Furthermore, the compression speed of 50-60 mm/s may have produced a low flatness of the half-pallet in this study.

Semi-crystalline polymers develop higher amounts of residual stress and part distortion (warpage) compared to amorphous polymers due to their crystalline nature. Additionally, the FDM processing parameters such as ambient temperature play an important role in the resulting residual stresses and part distortion of the printed part. Hence, in this study, the effect of ambient temperature on the in-built residual stresses and warpage of amorphous acrylonitrile-butadiene-styrene (ABS) and semi-crystalline polypropylene (PP) polymers was investigated. From the results, it was observed that increasing the ambient temperature from 50 °C to 75 °C and further to 120 °C resulted in 0.22-KPa and 0.37-KPa decreases in residual stress of ABS, but no significant change in the amount of warpage. For PP, increasing ambient temperature from 50 °C to 75 °C led to a more considerable decrease in residual stress (0.5 MPa) and about 3% increase in warpage. Further increasing to 120 °C resulted in a noticeable 2 MPa decrease in residual stress and a 3.4% increase in warpage. Reduction in residual stress in both ABS and PP as a result of increasing ambient temperature was due to the reduced thermal gradients. The enhanced warpage in PP with increase in ambient temperature, despite the reduction in residual stress, was ascribed to crystallization and shrinkage.

To analyze the effects of nonlinear behavior characteristics of prepreg (PPG) among the insulating materials of substrate and the residual stress of laminating process on the warpage of substrate, this study investigated the continuous laminating process using the numerical analysis by finite element method. The analysis results showed that the warpage of the substrate in the laminating process of PPG was very low, but it increased rapidly in the solder resist (SR) laminating process. As the laminating process of PPG continued, the stress inside the substrate increased continuously and it was predicted to decrease in the SR laminating process. These results confirmed that the warpage of the substrate is influenced the most by the SR laminating process, and that the warpage and stress of substrate accumulated in the laminating process of PPG have significant effects on the final warpage.

Plastics are commonly used engineering materials, and the injection-molding process is well known as an efficient and economic manufacturing technique for producing plastic parts with various shapes and complex geometries. However, there are certain manufacturing defects related to the injection-molding process, such as short shot, shrinkage, and warpage. This research aims to find optimum process parameters for high-quality end products with minimum defect possibility. The Artificial Neural Network and Taguchi Techniques are used to find a set of optimal process parameters. The Analytic Hierarchy Process is used to calculate the weight of each defect in the proposed thin-walled part. The Finite Element Analysis (FEA) using SolidWorks plastics is used to simulate the injection-molding process for polypropylene parts and validate the proposed optimal set of process parameters. Results showed the best end-product quality was achieved at a filling time of 1 s, cooling time of 3 s, pressure-holding time of 3 s, and melt temperature of 230 °C. The end-product quality was mostly influenced by filling time, followed by the pressure-holding time. It was found that the margin of error for the proposed optimization methods was 1.5%, resulting from any uncontrollable parameters affecting the injection-molding process.

Fused deposition modeling (FDM) is one of the most affordable and widespread additive manufacturing (AM) technologies. Despite its simplistic implementation, the physics behind this FDM process is very complex and involves rapid heating and cooling of the polymer feedstock. As a result, highly non-uniform internal stresses develop within the part, which can cause warpage deformation. The severity of the warpage is highly dependent on the process parameters involved, and therefore, currently extensive experimental studies are ongoing to assess their influence on the final accuracy of the part. In this study, a thermomechanical Finite Element model of the 3D printing process was developed using ANSYS. This model was compared against experimental results and several other analytical models available in the literature. The developed Finite Element Analysis (FEA) model demonstrated a good qualitative and quantitative correlation with the experimental results. An L9 orthogonal array, from Taguchi Design of Experiments, was used for the optimization of the warpage based on experimental results and numerical simulations. The optimum process parameters were identified for each objective and parts were printed using these process parameters. Both parts showed an approximately equal warpage value of 320 μm, which was the lowest among all 10 runs of the L9 array. Additionally, this model is extended to predict the warpage of FDM printed multi-material parts. The relative percentage error between the numerical and experimental warpage results for alternating and sandwich specimens are found to be 1.4% and 9.5%, respectively.

This study focuses on applying intelligent modeling methods to different injection molding process parameters, to analyze the influence of temperature distribution and warpage on the actual development of auto locks. It explores the auto locks using computer-aided engineering (CAE) simulation performance analysis and the optimization of process parameters by combining multiple quality characteristics (warpage and average temperature). In this experimental design, combinations were explored for each single objective optimization process parameter, using the Taguchi robust design process, with the L 18 (2 1 ) orthogonal table. The control factors were injection time, material temperature, mold temperature, injection pressure, packing pressure, packing time, cooling liquid, and cooling temperature. The warpage and temperature distribution were analysed as performance indices. Then, signal-to-noise ratios (S/N ratios) were calculated. Gray correlation analysis, with normalization of the S/N ratio, was used to obtain the gray correlation coefficient, which was substituted into the fuzzy theory to obtain the multiple performance characteristic index. The maximum multiple performance characteristic index was used to find multiple quality characteristic-optimized process parameters. The optimal injection molding process parameters with single objective are a warpage of 0.783 mm and an average temperature of 235.23 °C. The optimal parameters with multi-objective are a warpage of 0.753 mm and an average temperature of 238.71 °C. The optimal parameters were then used to explore the different cooling designs (original cooling, square cooling, and conformal cooling), considering the effect of the plastics temperature distribution and warpage. The results showed that, based on the design of the different cooling systems, conformal cooling obtained an optimal warpage of 0.661 mm and a temperature of 237.62 °C. Furthermore, the conformal cooling system is smaller than the original cooling system; it reduces the warpage by 12.2%, and the average temperature by 0.46%.7 ) orthogonal table. The control factors were injection time, material temperature, mold temperature, injection pressure, packing pressure, packing time, cooling liquid, and cooling temperature. The warpage and temperature distribution were analysed as performance indices. Then, signal-to-noise ratios (S/N ratios) were calculated. Gray correlation analysis, with normalization of the S/N ratio, was used to obtain the gray correlation coefficient, which was substituted into the fuzzy theory to obtain the multiple performance characteristic index. The maximum multiple performance characteristic index was used to find multiple quality characteristic-optimized process parameters. The optimal injection molding process parameters with single objective are a warpage of 0.783 mm and an average temperature of 235.23 °C. The optimal parameters with multi-objective are a warpage of 0.753 mm and an average temperature of 238.71 °C. The optimal parameters were then used to explore the different cooling designs (original cooling, square cooling, and conformal cooling), considering the effect of the plastics temperature distribution and warpage. The results showed that, based on the design of the different cooling systems, conformal cooling obtained an optimal warpage of 0.661 mm and a temperature of 237.62 °C. Furthermore, the conformal cooling system is smaller than the original cooling system; it reduces the warpage by 12.2%, and the average temperature by 0.46%.

Warpage is a typical defect for injection-molded parts, especially for crystalline parts molded by rapid heat cycle molding (RHCM). In this paper, a prediction method is proposed for predicting the warpage of crystalline parts molded by the RHCM process. Multi-layer models were established to predict warpage with the same thicknesses as the skin-core structures in the molded parts. Warpages were defined as the deformations calculated by the multi-layer models. The deformations were solved using the classical laminated plate theory by Abaqus. A model was introduced to describe the elastic modulus with the influence of temperature and crystallinity. The simulation process was divided into two procedures, before ejection and after ejection. Thermal stresses and thermal strains were simulated, respectively, in the procedure before ejection and after ejection. The prediction results were compared with the experimental results, which showed that the average errors between predicted warpage and average experimental warpage are, respectively, 7.0%, 3.5%, and 4.4% in conventional injection molding (CIM), in RHCM under a 60 °C heating mold (RHCM60), and in RHCM under a 90 °C heating mold (RHCM90).

Shrinkage and warpage of injection-molded parts can be minimized by applying microcellular foaming technology to the injection molding process. However, unlike the conventional injection molding process, the optimal conditions of the microcellular foam injection molding process are elusive because of core differences such as gas injection. Therefore, this study aims to derive process conditions to minimize the shrinkage and warpage of microcellular foam injection-molded parts made of glass fiber reinforced polyamide 6 (PA6/GF). Process factors and levels were first determined, with experiments planned accordingly. We simulated designed experiments using injection molding analysis software, and the results were analyzed using the Taguchi method, analysis of variance (ANOVA), and response surface methodology (RSM), with the ANOVA analysis being ultimately demonstrating the influence of the factors. We derived and verified the optimal combination of process factors and levels for minimizing both shrinkage and warpage using the Taguchi method and RSM. In addition, the mechanical properties and cell morphology of PA6/GF, which change with microcellular foam injection molding, were confirmed., Competing Interests: The authors declare no conflict of interest.

The usage of recycled polymers for industrial purposes arises as one of the most promising methods of reducing environmental impact and costs associated with scrapping parts. This paper presents a systematic study of the dimensional stability of a raw and 100% recycled polypropylene subjected to realistic environmental conditions occurring along its working life. The component studied is an internal part of an induction hob assembly. Industrial samples manufactured with both materials, in the same mold, and in the same injection machine, are subjected to ejection conditions, storage conditions (50 °C), and extreme performance conditions (80 °C). Induced dimensional changes are registered and analyzed using a coordinate measuring machine, and a tactile sensing probe. To verify the process capability of the samples manufacturing, C p and C pk values are calculated to evaluate the suitability of the recycled material as an alternative. Results conclude that, although the use of recycled material implies slight differences in terms of dimensional stability due to the changes induced in the polymer structure, these differences are not significant enough to affect the injection process capability. Therefore, recycling arises as one effective method to reduce both overruns associated with the consumption of raw polypropylene material and its environmental impact.