Search Results (226)

Binder jetting additive manufacturing (BJAM) offers an effective approach for fabricating silicon carbide (SiC) parts with complex geometries; however, part quality is strongly influenced by process variables. Binder saturation and drying time are key process variables in BJAM, yet their individual influences on the density and dimensional deviation of SiC green parts remain underexplored. To address this gap, this study systematically investigates the effects of binder saturation and drying time on the dimensional deviation and density of SiC green parts by evaluating four binder saturation levels (60%, 80%, 100%, and 120%) and three drying times (15, 30, and 45 s). The results show that increasing binder saturation reduces green part density and increases dimensional deviation, whereas increasing drying time improves density and reduces dimensional deviation. Excessive drying, however, causes severe warpage, preventing the fabrication of dimensionally accurate parts. These findings highlight the need to optimize binder saturation and drying time to improve the density of printed parts while minimizing dimensional deviation. Full article

In this paper, an AZ31B Mg/Al clad plate with 5052 aluminum alloy as the cladding was successfully prepared by a new composite process of corrugated roll roughing + flat roll finishing. First, finite element simulation software was used to predict and analyze the rolling process. Subsequently, experimental research was carried out according to the simulation results, and clad plate samples under single corrugated rolling and corrugated–flat rolling processes were prepared. Finally, the differences between the two clad plates in shape quality, interface bonding state, and mechanical properties were systematically compared and analyzed. The results show that, compared with the traditional corrugated rolling process, the sheet formed by corrugated–flat rolling composite rolling has a flatter shape with no warpage, and its interface bonding quality is better. The specific performance is as follows: the mechanical properties were significantly improved, and the tensile strength and elongation reached 259.96 MPa and 8.11%, respectively, in the transverse direction (TD). This study provides a new strategy for the preparation of high-performance Mg/Al clad plates. Full article

Printing with high-performance polymers such as polyether ether ketone (PEEK) and polyetherimide (PEI) presents issues regarding shrinkage and warpage due to elevated temperatures. One method highlighted to mitigate against this is through polymer blending. This study explores the development and characterization of PEEK and PEI blends as filament for fused filament fabrication (FFF) in additive manufacturing. Filaments were produced via melt extrusion using PEEK/PEI weight ratios 100/0, 80/20, 70/30, 60/40, 50/50, 40/60, 20/80, and 0/100 (wt.%). The aim is to identify an optimum blend which enhances printability and maintains mechanical and thermal integrity. The extruded filaments were first characterized through differential scanning calorimetry (DSC) to determine miscibility with all ratios presenting a single glass transition temperature. Samples were then 3D-printed and assessed through mechanical testing, DSC, X-ray diffraction (XRD), and scanning electron microscopy (SEM). The PEEK/PEI 80/20 (wt.%) blend was recognized as the optimum blend for maintaining crystallinity (35%) as well as good mechanical properties, averaging ultimate tensile strengths (UTSs) of 75.6 MPa and a Young’s modulus of 1338 MPa. Thermal properties also improved while warpage reduced and printability improved. Full article

The growing interest in sustainable additive manufacturing has driven research into customized biocomposite filaments reinforced with natural fibers. This study evaluates the influence of flax fiber content (5–15 wt%) on the thermal, rheological, morphological, and mechanical properties of fully bio-based polyamide PA10.10 filaments intended for fused deposition modeling (FDM). Filaments containing up to 15 wt% flax fibers were produced using both conventional single-screw extrusion and the METEOR^® elongational mixer to compare shear- and elongation-dominated dispersive mechanisms. Increasing flax loading enhanced stiffness (up to +84% tensile modulus at 15 wt%) but also significantly increased porosity, particularly in METEOR-processed materials, leading to reduced strength and intrinsic viscosity. Microscopy confirmed fiber shortening during compounding and revealed porosity arising from moisture release and insufficient fiber wetting. Rheological analysis showed the onset of a pseudo-percolated fiber network from 10 wt%, while excessive porosity at higher loadings impeded melt flow and printability. Based on the combined evaluation of the mechanical performance, dimensional stability, and processability, a 5 wt% flax formulation was identified as the optimal compromise for FDM. A functional automotive demonstrator (Fiat 500 dashboard fascia) was successfully printed using optimized FDM parameters (nozzle 240 °C, bed 75 °C, speed 20 mm s⁻¹, 0.6 mm nozzle, 0.20 mm layer height, and 100% infill). The part exhibited controlled shrinkage and limited warpage (maximum 1.8 mm across a 165 × 180 × 45 mm geometry with a 3 mm wall thickness). Dimensional accuracy remained within ±0.7 mm relative to the CAD geometry. These results confirm the suitability of PA10.10/flax biocomposites for sustainable, lightweight automotive components and provide key structure–processing–property relationships supporting the development of next-generation bio-based FDM feedstocks. Full article

Injection molding is a high-volume manufacturing process widely used for producing polymer components; however, its process parameters strongly influence residual stress, warpage, and the resulting mechanical performance. This work presents a comprehensive factorial design and ANOVA to evaluate the simultaneous effects of the injection temperature, packing pressure, packing time, and specimen orientation on the warpage, hardness, tensile, and flexural properties of polypropylene plates. The results demonstrate that the injection temperature and packing pressure are the dominant factors affecting the hardness and ultimate tensile strength, whereas warpage is mainly governed by the injection temperature and orientation. Under the tested conditions, certain combinations of injection temperature and packing pressure led to an improved mechanical performance; however, these adjustments also produced reductions in other properties, indicating that the balance among parameters depends on the targeted application rather than a single optimal set. Conversely, the parameter combination that produced the lowest warpage still yielded a significant increase in $E_{sec}$, indicating that reducing the warpage does not necessarily compromise the tensile stiffness. Interestingly, variations in the stress distribution between the tensile and bending tests suggest that the solidification-induced structure of the material influences its mechanical response, with specimens that showed a lower tensile strength exhibiting a comparatively higher resistance under bending. These findings provide new insights into the trade-offs between dimensional accuracy and mechanical performance and offer practical guidelines for optimizing polypropylene injection molding processes. Full article

In this study, the thermal and structural behavior of battery module components produced from polymer-based composites was systematically evaluated using coupled Moldflow 2016 and ANSYS Fluent 2024 simulations. Three thermoplastics—metal-flake-reinforced PC+ABS (Polycarbonate/Acrylonitrile Butadiene Styrene), carbon-fiber-reinforced PEEK (Polyether Ether Ketone), and hybrid mineral-filled PP (Polypropylene)—were investigated as alternatives to conventional aluminum components. Moldflow simulations enabled the assessment of injection molding performance by determining injection pressure, volumetric shrinkage, warpage, residual stress, flow front temperature, and part weight. PEEK exhibited the best dimensional stability, with minimal warpage and shrinkage, while PP showed significant thermomechanical distortion, indicating poor resistance to thermally induced deformation. For thermal management, steady-state simulations were performed on a 1P3S pouch cell battery configuration using the NTGK/DCIR model under a constant heat load of 190 W. Material properties, including temperature-dependent thermal conductivity, density, and specific heat capacity, were defined based on validated databases. The results revealed that temperature distribution and Joule heat generation were strongly influenced by thermal conductivity. While aluminum exhibited the most favorable thermal dissipation, PC+ABS closely matched its electrical performance, with only a 1.3% lower average current magnitude. In contrast, PEEK and PP generated higher cell core temperatures (up to 20 K) due to limited heat conduction, although they had comparable current magnitudes imposed by the energy-conserving model. Overall, the findings indicate that reinforced thermoplastics, particularly PC+ABS, can serve as lightweight and cost-effective alternatives to aluminum in mid-range battery modules, providing similar electrical performance and thermal losses within acceptable limits. Full article

This study focuses on the design and optimization of a cooling layer system integrated into a thin-thickness mold insert to enhance heat transfer efficiency, control mold temperature, and improve the quality of composite products during injection molding. The Taguchi method with an L25 (5⁴) orthogonal array was employed to investigate four key parameters: insert thickness, cooling layer thickness, water flow rate, and coolant temperature. Among 25 experimental combinations, five representative cases were selected for detailed analysis. The results indicate that the optimal configuration (0.5 mm insert, 10 mm cooling layer, 3.5 L/min flow rate, and 80 °C coolant temperature) successfully maintained a high and stable mold temperature, with a cavity temperature difference of only 3.6 °C at steady state and a simulation–experiment deviation ranging from 2.4% to 7.2%. This condition not only improved melt flowability and surface quality but also reduced defects such as weld lines, warpage, and shrinkage. In parallel, displacement measurements on PA6 and glass fiber-reinforced PA6 (PA6 + GF) composites revealed that increasing the fiber content from 0% to 30% reduced output displacement by more than 19% compared to neat PA6, highlighting the reinforcing effect of glass fibers and the relationship between temperature distribution and mechanical displacement behavior. The findings confirm that integrating a cooling layer into a thin-thickness mold, combined with Taguchi-based optimization, provides an effective approach to enhance through-thickness heat transfer, reduce deformation, and ensure the overall quality of composite injection-molded products in industrial applications. Full article

During the Fused Deposition Modeling (FDM) molding process, temperature changes are nonlinear and instantaneous, which is a key parameter affecting FDM printing efficiency, molding accuracy, warpage deformation, and other factors. This study presents a finite element simulation framework that integrates ANSYS Parametric Design Language (APDL) with birth–death element technology to investigate the temperature evolution and thermomechanical behavior during the FDM process. The framework enables dynamic simulation of the complete printing and cooling cycle, capturing the layer-by-layer material deposition and subsequent thermal history. Results indicate that temperature distribution follows a gradient pattern along the printing path, with rapid heat dissipation at the periphery and heat accumulation in the central regions. Thermomechanical coupling analysis reveals significant stress concentration at the part bottom (310 MPa) and progressive strain increase from bottom (3.68 × 10⁻⁵ m) to top (2.95 × 10⁻⁴ m). Experimental validation demonstrates strong agreement with numerical predictions, showing maximum temperature deviations below 8% and strain distribution errors within 5%. This integrated approach provides an effective tool for predicting thermal-induced deformations and optimizing FDM process parameters to enhance part quality. Full article

In this work, the influence of glass fibers on the performance of the injection molding process for a PA6-based AR15/M4 grip was investigated numerically. The process was realistically modeled using Autodesk Moldflow Insight for different glass fiber percentages (0 wt%, 15 wt%, 30 wt%, 45 wt%). The simulation results were evaluated, including the temperature distribution, flow time, pressure drop, pumping power, volumetric shrinkage and warpage displacement. The findings indicate that, with 15 wt% glass fibers, the material exhibits the shortest fill period (0.62 s) and the lowest pressure drop (0.0061 MPa) and power consumption (0.000433 kW), indicating maximum flow efficiency. On the other hand, a 30 wt% GF setup exhibited the largest volumetric shrinkage (17.76% at most) and warpage (Y: 1.213 mm), even though it had better thermal conductivity. The 45 wt% GF material exhibited the lowest amount of shrinkage and distortion but led to a greater energy consumption compared to 30 wt% GF. Overall, the 15 wt% GF grade provided the highest average process efficiency and dimensional accuracy; therefore, it is the most appropriate grade for precision molded firearm components. Full article

A critical aspect in the design of power electronics packages is the prediction of their mechanical response under severe thermomechanical loads and the consequent structural damage. For this purpose, finite element (FE) simulations are used to estimate the mechanical performance and reliability under operational conditions, typically alternate high voltages/currents resulting in thermal gradients. When simulations are performed, it is common practice to consider the as-received package to be in a stress-free state. Namely, residual stresses and plastic deformation induced by the manufacturing processes are neglected. In this study, an advanced FE modeling approach is proposed to assess the structural consequences of the encapsulating resin curing, typical in the production of silicon carbide (SiC)-based power electronics modules for electric vehicles. This work offers a general modeling framework that can be further employed to simulate the effects of thermal gradients induced by the production process on the effective shape and residual stresses of the as-received package for other manufacturing stages, such as metal brazing, soldering processes joining copper and SiC, and, to lower extents, the application of polyimide on top of passivation layers. The obtained results have been indirectly validated with experimental data from literature. Full article

Thermal cycling test is one of the reliability tests, which are important for metal-ceramic layered composites (metallized ceramic substrates), a part in power modules. Since thermal cycles are within a large range of temperature, the test has only been performed using a thermal chamber. It limited the understanding of degradation mechanism in metallized ceramics substrates. Among NDE techniques, Digital Image Correlation (DIC) is a simple and effective method, enhanced by modern digital imaging technologies, enabling precise measurements of displacement, strain, deformation, and defects with a simple setup. In this paper, we combined some of our previous work to make a review to present a full analysis of a silicon metallized substrate under thermal cycling test (from beginning to fail) using DIC method. The main content is the application of DIC in evaluating the reliability of metallized silicon nitride (AMB-SN) substrates under thermal cycling with temperatures from −40 °C to 250 °C. Three key aspects of the AMB-SN substrate are presented, including (i) thermal strain characteristics before and after delamination, (ii) warpage and dynamic bending behavior across damage states, and (iii) stress–strain behavior of constituent materials. The review provides insights into degradation progress of the substrate and the role of Cu in substrate failure, and highlights DIC’s potential in ceramic composites, offering a promising approach for improving reliability test simulations and advancing digital transformation in substrate evaluation, ultimately contributing to enhanced durability in high-power applications. Full article

While material extrusion via fused filament fabrication (FFF) offers design flexibility and rapid prototyping, its practical use in engineering is limited by mechanical challenges, including residual stresses, geometric distortions, and potential interlayer debonding. These issues arise from the dynamic thermal profiles during FFF, including temperature gradients, non-uniform hardening, and rapid thermal cycling, which lead to uneven internal stress development depending on fabrication parameters and object topology. These problems can compromise the structural integrity and mechanical properties of FFF parts, especially when the load-bearing capacity and geometric accuracy are critical. This study focuses on polylactic acid (PLA) due to its widespread application in engineering. It introduces a computational framework for coupled thermo-mechanical simulations of the FFF process using ABAQUS (Version 2020) finite element software. A key innovation is an automated subroutine that converts G-code into a time-resolved event series for finite element activation. The simulation framework explicitly models the sequential stages of printing, cooling, and detachment, enabling prediction of adhesive loss and post-process warpage. A transient thermal model evaluates the temperature distribution during FFF, providing boundary conditions for a mechanical simulation that predicts residual stresses and warping. Uniquely, the proposed model incorporates the detachment stage, enabling a more realistic and experimentally validated prediction of warpage and residual stress release in FFF-fabricated components. Although the average deviation between predicted and measured displacements is about 10.6%, the simulation adequately reflects the spatial distribution and magnitude of warpage, confirming its practical usefulness for process optimization and design validation. Full article

In this research, the thermal and structural responses of high-performance dielectric strength polymers in the injection molding process for multi-pin electrical connectors were thoroughly studied using Moldflow simulations and optimized via a Box–Behnken experimental design under the Response Surface Methodology (RSM). Injection molding analyses were performed on Polyether-ether-ketone (PEEK), Polyetherimide (PEI), and Polyamide-imide (PAI) polymers using the MS3102A 16S-1P electrical connector model. In the conducted simulations, the melt temperature, injection time, and mold open time were evaluated as three fundamental process parameters through multivariate analysis. The volumetric shrinkage, sink mark depth, residual stress, warpage, and surface temperature homogeneity were considered as the major output qualities. According to the results, the PAI material provided superior thermal stability with an average heat removal capacity of 0.127 kW, whereas the PEI material exhibited the most homogeneous cooling behavior with a surface temperature of 45.5 °C. The minimum warpage was found to be 0.254 mm, whereas the sink mark depth was recorded within the range of 0.018–0.031 mm and the rate of volume shrinkage was between 1.03% and 1.41% in the investigations. The PAI material gave the maximum residual stress of 81.9 MPa in oriented regions of the mold. This study fills a considerable gap in the field by investigating material choice and process parameter adjustments via multivariate analysis, particularly for decision making in the production of high-reliability electrical components. Full article

During the cooling phase of injection molding, the conformal cooling channel system optimizes the uniformity of mold temperature, diminishes warping deformation, and contributes substantially to heightened product precision. The injection molding process involves complex process parameters that may result in uneven cooling between components, leading to prolonged cycle times, increased shrinkage depth, and warping deformation of the plastic parts. These manifestations negatively impact the surface quality and structural strength of the final product. This article combined theoretical algorithms with finite element simulation (CAE) methods to optimize complex injection molding processes. Firstly, the characteristics of six different types of materials were examined. Melt temperature, mold opening time, injection time, holding time, holding pressure, and mold temperature were chosen as optimization variables. Meanwhile, the warpage deformation and shrinkage depth of the formed sample were selected as optimization objectives. Secondly, an L27 orthogonal experimental design (OED) was established, and the signal-to-noise ratio was processed. The entropy weight method (EWE) was used to calculate the weights of the total warpage deformation and shrinkage depth, thereby obtaining the grey correlation degree. The influence of process parameters on quality indicators was analyzed using grey relational analysis (GRA) to calculate the range. A second-order polynomial regression model was established using response surface methodology (RSM) to investigate the effects of six factors on the warpage deformation and shrinkage depth of injection molded parts. Finally, a comprehensive comparison was made on the impact of various optimization methods and models on the forming parameters. Analyze according to different optimization principles to obtain the corresponding optimal process parameters. The research results indicate that under the principle of prioritizing warpage deformation, the effectiveness ranking of the three optimization analyses is RSM > OED > GRA. The minimum deformation rate is 0.1592 mm, which is 27.37% lower than before optimization. Under the principle of prioritizing indentation depth, the effectiveness ranking of the three optimization analyses is OED > GRA > RSM. The minimum depth of shrinkage is 0.0312 mm, which is 47.21% lower than before optimization. This discovery provides strong support for the optimal combination of process parameters suitable for production and processing. Full article

In recent years, many electronic device industries have shown interest in using artificial intelligence (AI) to quickly estimate package warpage. Machine learning is one of the AI techniques which will give an express prediction on package warpage with the help of several attributes of the data and different algorithms. This study uses a deep learning (DL) model which combines with a deep neural network (DNN) technique and finite element analysis (FEA) to estimate the package warpage of a mobile universal flash storage (UFS) package. Developing a DL model requires a training database from finite element simulation results and a DNN algorithm. The developed DL model accuracy for package warpage is calculated by validating FEA simulation results and experiment data. The error between the DL model prediction and FEA simulation result is less than 7%. This proposed approach can help effectively and efficiently assess package warpage for new product introduction (NPI) with less FEA simulation work and less test vehicle of a real package for warpage measurement and assessment. Full article