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This paper proposes an interpretation methodology for the effect of transient process data on quality of injection molded parts. The transient process data measured in the actual processing space have been regarded as the most relevant information to manufacturing processes and product quality. However, its interpretation to pinpoint which feature in the data would affect part quality has traditionally relied on knowledge and understanding of the manufacturing process. The main objective of this method is to reduce the dependency of the transient process data analysis on process knowledge and understanding by using explainable artificial intelligence (XAI). The contribution of the 'section-wise' features in the transient process data to the quality prediction of machine learning (ML) models was investigated for the first time. The interpretation results of the effect of cavity pressure and mold surface temperature on four different quality factors represented reasonable explanations of the characteristics of the polymer materials, product geometry, and molding process. Due to the intermediate relationship of the transient process data with the user-specified process parameters and the resulting quality variables, the interpretation results can be further utilized to optimize the process and provide the optimal transient process data profile for best part quality. [ABSTRACT FROM AUTHOR]

Injection molding is widely used for making intricate plastic products due to its precision, cost efficiency, and fast production. Industries like consumer electronics, aerospace, and medical, demand high mechanical properties from these parts. However, high‐performance polymers face challenges in flowability. Ultrasonic‐assisted injection molding offers a solution, but its impact on flowability and mechanical properties is not fully understood. We propose a novel injection mold design with in‐mold ultrasonic vibration to address this. By applying high‐frequency shear forces to the melt, it alters polymer chain alignment, enhancing flow and microstructure. Employing polyphenylene sulfide (PPS) resin as the primary material, this study systematically explores the impact of varying ultrasonic vibration durations and stages on melt filling behavior and product performance. Compared with conventional molds, ultrasonic‐assisted molds reduce melt viscosity by 38% and improve mechanical properties by 10.21%, with a 17.1% increase in crystallinity. This technology shows promise for improving flowability and mechanical properties in injection molding, with potential for wide industrial application. [ABSTRACT FROM AUTHOR]

In water‐assisted injection molding processes, it is crucial to understand the mechanisms governing the formation of hollow structures and identify the key factors influencing their morphology and dimensional accuracy. This work combined experimental analysis and numerical simulation to investigate the influence of different mold cavities and main processing parameters on hollow structures in overflow water‐assisted injection molded parts of short‐glass‐fiber‐reinforced polypropylene, that is, hollow shape and hollow ratio. The results show that the hollow shape and hollow ratio depended not only on the cross‐sectional location but also on the cross‐sectional shape of the mold cavity. For the circular parts, the hollow shape resembled the cross‐sectional shape of the mold cavity, with a relatively small and uniform hollow ratio across cross‐sectional locations. For the noncircular parts, the hollow shape varied considerably with increasing distance from the water inlet. Moreover, the results also show that except for the influence of water‐injection delay time on the uniformity of the hollow ratio, higher melt temperature (250°C), shorter water‐injection delay time (0 s), and higher water pressure (10 MPa) contributed to the hollow shape being closer to the cross‐sectional shape of mold cavities and made hollow ratios relatively larger and more uniform. [ABSTRACT FROM AUTHOR]

The stability of the injection molding process is critical to efficient production. However, environment and production disturbances pose challenges to maintaining a stable molding process. A two-stage dynamic adjustment strategy is proposed in this paper to increase weight consistency, considering fluctuation of density and fluidity based on products' types and structure. This study investigates the factors influencing the weight stability of injection molding products during the injection and holding stages. Experiments show that the injection stage is affected by density fluctuations, while melt fluidity fluctuations influence the holding stage. Simulation experiments prove the efficacy of dynamic adjustment strategies for injection-sensitive products (ISP) and holding-sensitive products (HSP). Thinner products as ISPs benefit from adjustments of the injection stage parameters, while thicker products as HSPs require optimization of holding stage parameters. To prove its validity, this strategy was tested on two molds and improved weight stability by 60.0% and 34.8%, respectively. [ABSTRACT FROM AUTHOR]

The development of innovative composite materials through the amalgamation of thermoplastic polyurethane (TPU) with bismuth sodium titanate (BNT) and carbon nanotube (CNT) fillers was investigated. Before the composite fabrication, the fillers' surfaces were treated to enhance their compatibility with the TPU matrix. Hybrid fillers of BNT and CNTs were fabricated by mixing the two types of filler particles through ball milling and subsequently annealing the mixture at 250°C. Melt‐blending and injection molding were utilized to synthesize the composites at 210°C processing temperature. The prepared composites showed significantly enhanced thermal conductivity, dielectric constant, thermal stability, and thermomechanical properties compared with the neat TPU matrix. For instance, the dielectric constant was enhanced by 340% upon the inclusion of 40 wt.% BNT and CNT fillers compared to the neat TPU matrix (40CBNT‐TPU has 13.2). In particular, the inclusion of BNT‐CNT particles in the TPU matrix improved the thermal conductivity of the TPU matrix by 1180% tremendously as compared to neat TPU (40CBNT‐TPU has 2.6 W/(m.K)). Highlights: Crystalline bismuth sodium titanate (BNT) is fabricated.Degradation of 8 wt.% of the IPDI‐treated BNT proves surface treatment.Dielectric constant (DC) improved by 340% compared to neat TPU.Thermal conductivity (TC) enhanced 11.4 times compared to neat TPU.Improvement in TC and DC will make it applicable in electronic materials. [ABSTRACT FROM AUTHOR]

AbstractTo improve the epoxy bonding properties of polyphenylene sulfide (PPS) matrix composites, CK-MMT and K-BF were prepared by modifying montmorillonite (MMT) and basalt fiber (BF) with cetyl trimethyl ammonium bromide (CTAB) and 3-Glycidyloxypropyltrimethoxysilane (KH-560) as the modifiers. CK-MMT/BF/TPU/PPS composites were prepared by injection moulding. The surface properties of the composites were tested and characterized by scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS), etc. The epoxy bonding and mechanical properties were studied by combining the single-lap-joint tensile shear strength test and notched impact test. The results demonstrated the successful preparation of the modified MMT and BF. With the addition of CK-MMT and K-BF in different ratios, the surface roughness and the contents of polar groups of the composites increased, which could effectively improve the epoxy bonding properties of PPS matrix composites. When the additions of CK-MMT and K-BF were 10 and 25 wt%, respectively, the composites had the best overall properties. It demonstrated a single-lap-joint tensile shear strength was 7.56 MPa, representing a 220.34% increase over that of thermoplastic polyurethane/polyphenylene sulfide (TPU/PPS) and a 477.10% increase over that of pure PPS. [ABSTRACT FROM AUTHOR]

This study is a comparative assessment of polypropylene composites reinforced with two different range size of Agave Americana fibers. The first is from 125 to 630 microns, named as Short Agave Fiber (SHAF), and the second range is beyond 630 microns, named as Long Agave Fiber (LAF). The composites were produced by twin-screw extrusion and injection molding processes. The composite manufacturing by this interior part of plant agave fibers is mentioned in the first time in the literature. The fiber content for the SHAF and LAF composites was chosen as 10 wt. %. It was found that better mechanical properties were achieved with LAF composite which increased by 301.4% compared with the neat PP. This was explained by LAF features compared to SHAF such as the higher cellulose content LAF (73.5%) and SHAF (40.3%), the higher crystallinity index was obtained better thermal stability which led to a composite which is more crystalline, more thermally stable and stiffer. This was explained by the good interfacial adhesion between fibers and the matrix revealed by SEM analysis. [ABSTRACT FROM AUTHOR]

Warpage of the injection moulded parts is one of the most common defects after demoulding, which is intensively present in thin-walled moulded parts or parts with non-uniform wall thickness. The level of the warpage can be reduced by optimizing the mould tempering system in the phase of mould design, by optimizing the injection moulding parameters and recently by optimizing the shape of the mould cavity elements geometry – so-called inverse contouring. Computer simulation of injection moulding process can show the level of moulded part warpage after ejection from the mould, but it will not allow detailed measuring of critical moulded part measures deviations. Detailed analysis and prediction of the critical moulded part dimensions can be performed by aligning of the deformed moulded part design obtained with computer simulation, with moulded part reference CAD geometry. This paper shows the main steps and an example of the geometry aligning process for a specific thermoplastic part. [ABSTRACT FROM AUTHOR]

In the injection molding process, the pressure within the mold cavity is crucial to the quality of the final product. Due to the inability to directly observe the process, sensor technology is required to acquire data. Traditionally, experts interpret and encode pressure curves, but this method has limitations. This study proposes an innovative pressure curve encoding technique to overcome these limitations and achieve automation to obtain more comprehensive pressure information. The study employs mold flow analysis software and autoencoders to capture and encode pressure data, classifying pressure curves into global pressure and local pressure values. Subsequently, a multilayer perceptron (MLP) neural network is used for machine learning to predict multiple qualities. Results indicate that local pressure features perform better in predicting multiple‐quality targets than global pressure features, exhibiting smaller prediction ranges and higher prediction stability. Although domain knowledge‐based indicator features slightly outperform in terms of predictive capability, the low error results of the local pressure feature method validate the effectiveness of the autoencoder approach, demonstrating its potential for digital information extraction and practical quality prediction in the injection molding process. Highlights: Develops a product quality prediction system for efficient injection molding.Autoencoders extract key features from pressure data without domain knowledge.ML models predict quality indicators, optimizing injection molding processes.Compares pressure features, showing data‐driven methods' prediction accuracy. [ABSTRACT FROM AUTHOR]

Liquid silicone rubber (LSR) is characterized by a wide range of advantageous properties and is therefore used in many branches and industries. However, the material is difficult to recycle due to the non‐reversible cross‐linking reaction. A promising approach to recycle the already cross‐linked (post‐industrial) waste is the mechanical recycling of LSR via grinding and addition of the powder as filler in virgin material. This research focused on the processing of such LSR‐powder‐compounds via injection molding and the influence of the powder content on mechanical properties. Compounds of virgin LSR and ambient ground powder were prepared and injection molded. Both the processability and the mechanical properties were analyzed. Compounds of up to 40 wt% powder content could be processed with standard injection molding machine equipment without any noticeable issues. The results show a similar compression set for the virgin as for the recycled compounds. Hardness decreases slightly but constantly. Tensile strength and elongation at break are at similar levels for all powder added compounds and drop only by 16.6% and 12.6% compared with the virgin LSR. The results are promising and should be the basis for further and more detailed investigations to industrialize the mechanical recycling of LSR. Highlights: Processing on standard injection molding machine with standard parameters.Up to 40 wt% recycled silicone powder content.Using recycled silicone particles has no effect on compression set.Tensile strength and elongation at break decrease only by 16.6% and 12.6%. [ABSTRACT FROM AUTHOR]

Manufacturing plastic parts with secondary feedstocks has risen to the forefront of importance in recent years. However, the variation in molecular weight and rheology of secondary feedstock can lead to inconsistent part quality. This work evaluates the effectiveness of a novel closed‐loop adaptive process control system that adjusts nozzle pressure in response to in‐mold pressure data. Five different recycled polypropylene blends, with a broad distribution of flow properties, were evaluated to determine the effectiveness of the control system at reducing processing variation. The experimental results show that the process control strategy reduced the variation within the mold, as seen by in‐mold pressure curves and calculated in‐mold viscosity values. Additionally, the parameters that control the automated process adjustments were investigated, showing the importance of optimization. The analysis of the correlation between in‐mold rheology and mechanical properties showed a slight variation in the mechanical properties and parts weight with a coefficient of variation of under 5%. Overall, the results demonstrate the ability of pressure‐controlled molding and automated viscosity adjustment to reduce the variability when molding a secondary feedstock. Highlights: Pressure‐controlled injection molding of recycled polypropylene.Automated closed‐loop adaptive process control methodology.Methodology resulted in a reduction in pressure variation during molding.Changes in mechanical properties and in‐mold viscosity were investigated.Results show the potential of pressure‐controlled molding at reducing variation. [ABSTRACT FROM AUTHOR]

The most frequently used method for measuring surface roughness is profilographometry. However, with complex and non-homogeneous surfaces, this method may be subject to large errors because of its contact nature and limitations related to the geometry of the measuring head. In this study, the surface topography was examined on polypropylene injection moldings produced using an injection mold with a complex molding cavity surface. The moldings were modified using a Nd:YAG laser, and the obtained structures were examined using two measurement methods, i.e. contact (profilographometry) and optical (3D digital microscopy). Researchers performed a statistical analysis to determine the differences between the measurement results obtained for the two methods. Additionally, the impact of the laser parameters on the modified surface was determined. The obtained results showed significant differences between the values of measurements made using different methods, especially in the case of surfaces that were modified by the laser beam to the greatest extent (laser A parameters). In all cases where a statistically significant difference was found between the measurement results, the mechanical method showed lower roughness values than the optical method, and the average difference between these results was 15%. [ABSTRACT FROM AUTHOR]

Most commercial software used to simulate the injection molding process of semi-crystalline thermoplastic polymers do not explicitly take into account the polymer crystallization, which could lead to errors in the estimations of filling as well as warpage and shrinkage. This is mainly due to the common complexity of the models used to describe crystallization and the challenging respective model parameter identification under injection molding conditions. To close this gap, in this work, we use a simple thermo-mechanical crystallization model to describe the flow-induced and quiescent crystallization of an unreinforced semi-crystalline thermoplastic material during injection molding. The crystallization model is implemented in the commercial software Autodesk® Moldflow® Insight 2021 using the Solver API feature alongside crystallization-dependent viscosity, PVT, and solidification models. The model parameters were identified using a calibration workflow that employs surrogate models representing the simulated pressure results to perform a multi-objective optimization. The filling predictions as well as the calculated pressure fields are presented using the calibrated model parameters in comparison to those measured during the actual injection molding of a polyoxymethylene (POM) part using different process conditions. The results show major improvements in the estimations of the time-depending pressure field as well as the level of filling of the produced parts. [ABSTRACT FROM AUTHOR]

In mass production, injection molding plays a vital role in manufacturing various parts with complex settings. As perfluoroalkoxy alkane (PFA) injection‐molded products are widely used in immersion system, dimensional quality needs more attention. However, there is limited research on the dimension defects of PFA injection‐molded products. This study focused on the influence of mold design and process parameters on PFA part shrinkage, using mold flow simulation and orthogonal testing separately. Several gate locations and sizes were simulated to minimize shrinkage in mold design. Displacements varied with gate locations, and shrinkage decreased with larger gate sizes. The Taguchi method analyzed process parameters' impact on shrinkage. The results indicated that the injection rate had the most significant effect on the shrinkage of tube length, while melt temperature, holding pressure, and screw speed affected the shrinkage of tubes' outside diameter. Different flow directions exhibited variance in shrinkage. Using max–min normalization, the two shrinkage values reached 0.00972, whereas the smallest value obtained in the orthogonal experiment was 0.1545 in run 3. Thus, optimizing mold design and process parameters were two effective methods to reduce shrinkage. This study reduced shrinkage and improved the quality of PFA injection molding parts for semiconductor systems. [ABSTRACT FROM AUTHOR]

The rapid development of new energy vehicles demands significant improvements in connector structures and performance standards. Wire harness connectors, crucial for linking various electrical components, face challenges due to their small size and thin-walled structure, which can lead to dimensional shrinkage and warping during injection molding. To address these issues, this study optimizes the injection molding process by fine-tuning parameters such as melt temperature, mold temperature, injection time, holding pressure/time, and cooling time. By integrating the Taguchi method with grey relational analysis, the study enhances the molding process for thin-walled composite connectors. This combined approach provides a comprehensive framework for optimizing multiple quality objectives and improving the overall performance of injection-molded composite components. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The effect of contamination of polypropylene (PP) with selected polymers is studied to simulate the effect of mis-sorting in recycling streams. Polystyrene (PS), polyethylene terephthalate (PET), polycarbonate (PC), acrylonitrile butadiene styrene (ABS), and polylactic acid (PLA) were compounded with PP at different concentrations varying between 3 and 10%. Infrared spectroscopy proved the absence of chemical bonds between the constituents. Generally, melt flowability, except for the PP/PLA blend, and crystallinity were only slightly affected by the incorporation of the contaminating polymers. Samples of the polymer blends were injection moulded and further tested for their tensile and impact properties. Critical behaviour was induced by the introduction of a weld line as a result of the application of multiple gating points during injection moulding. Results generally show the applicability of PP mixtures within the investigated range of contamination, without much sacrifice in mechanical performance. However, in the case of ABS and PLA, more care should be taken when designing complex parts with weld lines, due to reduced toughness. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the tribological characteristics of commercially available high-strength polyphthalamide-based composites with great contents (30–50 wt.%) of both carbon and glass fibers in point and linear contacts against metal and ceramic counterfaces under dry friction and oil-lubricated conditions at various loads and sliding speeds. The lengths of both types of fibers were varied simultaneously with their contents while samples were fabricated from granules by injection molding. When loading PPA with 30 wt.% SCFs at an aspect ratio (AR) of 200, the ultimate tensile strength and the elastic modulus increased up to 142.7 ± 12.5 MPa and 12.9 ± 0.6 GPa, respectively. In the composites with the higher contents of reinforcing fibers PPA/40CCF and AR~1000, the ultimate tensile strength and the elastic modulus were 240 ± 3 MPa and 33.7 ± 1.9 GPa, respectively. Under the applied test conditions, a composite reinforced with 40 wt.% carbon fibers up to 100 μm long at an aspect ratio of ~1000 possessed the best both mechanical properties and tribological characteristics. One of the reasons that should be considered for improving the tribological characteristics of the composite is the fatigue wear mechanism, which is facilitated by the high filling degree, the strong interfacial adhesion, and the great aspect ratio for fibers. Under the oil-lubricated conditions, both friction coefficients and wear rates decreased, so such friction units could be implemented whenever possible. The reported data can be used as practical recommendations for applying fibrous polyphthalamide-based composites as friction unit components. [ABSTRACT FROM AUTHOR]

The achievement of consistent molding quality, which is critical in injection molding, is heavily reliant on the reasonable control of processing materials, molds, machines, process parameters, and environmental conditions. Notably, new molds usually require a trial molding process before being delivered to relevant machines for online production. However, performance differences between machines make it challenging to maintain consistent molding quality, and suitable adjustments must be made to machine parameters to compensate for these differences. Therefore, cross-machine product quality prediction is critical for accurately forecasting product quality across different machines in a manufacturing process and thus for ensuring consistent quality, few defects, and optimized production. To avoid the considerable time and high cost required for quality inspection and to improve production efficiency, this study developed a multilayer perceptron (MLP) model combined with quality indices to predict molding quality. This paper describes how the developed model predicts product quality for the same mold in different machines. The procedure of the proposed MLP model involves four steps. First, data are prepared, features are extracted (extraction of quality indices), and the model is trained on an actual injection molding machine (machine A). Second, the developed MLP model establishes the relationships between the process parameters, quality indices, and product quality for machine A. Third, Moldex3D Studio, which is a software program for simulating injection molding, is employed to generate production data for a virtual injection molding machine (machine B). Finally, a transfer model is used to fit the quality indices of machines A and B so that the MLP model can directly predict the product quality (in terms of weight and geometric dimensions) for machine B on the basis of the quality indices generated using the process parameters of machine B. Experimental results indicate that the developed MLP model can accurately predict the weight and dimensions of products manufactured using different injection molding machines. In particular, the average error in predicting the product quality for machine B was found to be smaller than 0.5%, which indicates the feasibility of the developed model for cross-machine product quality prediction. [ABSTRACT FROM AUTHOR]

Various treatments, such as alkaline and silane treatments, are commonly applied to natural fillers before production to enhance their quality, thermal stability, and water absorption capacity and improve the fiber–matrix interface properties. However, these processes are not environmentally friendly and may escalate the production cost of composites due to the need for additional processing steps in mass production. This study delves into the impact of untreated walnut shell (WS) filler material, employed in varying ratios (ranging from 10 to 40%) as a filler, on the mechanical, thermal, morphological, and physical properties of environmentally friendly polylactic acid (PLA) matrix composites. The experimental results highlight a significant decrease in tensile modulus by 28%, tensile strength ranging from 32 to 65%, a decrease in flexural modulus by 22%, and flexural strength ranging from 24 to 58% with varying WS filler ratios. Time-dependent water absorption and increased density were observed. FT-IR analysis indicates structural similarities, while DSC results show minimal effects on glass transition temperature and crystallinity. TGA results reveal reduced thermal stability with increasing WS content. SEM microstructure imaging demonstrates homogeneous WS particle distribution, but higher WS content leads to increased brittleness and diminished resistance properties. In conclusion, this study underscores the importance of balancing sustainability through WS filler ratios while preserving mechanical performance. [ABSTRACT FROM AUTHOR]

Highlights Coir fiber (COIRF) reinforced glycidyl methacrylate (GMA) functionalized ethylene butyl acrylate (CF‐EBA) composites (COIRF/CF‐EBA) were processed by extrusion and injection molding. A good COIRF/CF‐EBA interfacial adhesion was indicated by Scanning Electron Microscopy (FE‐SEM). Fourier Transform Infra‐Red (FTIR) spectroscopy established this adhesion emerging from etherification and hydrogen bonding between the functional groups of CF‐EBA and of COIRF. The composites exhibited higher tensile properties than pristine CF‐EBA, and also exhibited increase in their tensile properties with increase in COIRF contents in them. The storage modulus and loss modulus of the composites also increased as the amount of COIRF in them increased, but the values of these properties decreased with increasing temperature. Thermal stability of the composites was observed to be intermediate between that of COIRF and CF‐EBA. Coir Fiber/Chemically Functionalized Ethylene Butylene Acrylate Composites. CF‐EBA/COIRF bonding by etherification and hydrogen bonding between them. The COIRF/CF‐EBA composites show higher properties than their CF‐EBA matrix. 30/70 COIRF/CF‐EBA composite showed the highest tensile strength (10.93 MPa). COIRF/CF‐EBA composite show thermal stability upto approx. 245°C. [ABSTRACT FROM AUTHOR]

Two series based on poly(propylene 2,5-furandicarboxylate)-block-poly(tetramethylene oxide) (PPF-b-F-PTMO) containing carbon and mineral nanofillers that differ in shape (1D and 2D) were synthesized via in situ polymerization. The influence of the addition of the 1D-type nanoparticle, i.e., carbon nanofibers (CNFs) and halloysite nanotubes (HNTs), and the so-called 2D-type, i.e., graphene nanoplatelets (GNPs) and organoclay (C20A), on the properties of a biobased block copolymer was analyzed. The dispersion of nanoadditives in the nanocomposites was determined using a scanning electron microscope (SEM). The thermal properties were studied employing differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). The introduction of nanoparticles increased the crystallinity (Xc) and the mean values of tensile modulus (E) of the bionanocomposites. In turn, one observed that the decrease in the limited viscosity number (LVN) was visible along with incorporating nanoadditives. The synthesized polymer bionanocomposites reveal the mechanical properties of elastomers during mechanical testing. Moreover, the good processability of the obtained materials by injection molding combined with the comprehensive ability to change mechanical and thermal properties of PPF-b-F-PTMO by tailoring the type and content of the nanofillers can indicate their possible applications in packaging, automotive, sports, construction, and many other industries. [ABSTRACT FROM AUTHOR]

Modern polymer‐based technical components not only have to fulfill demanding mechanical‐structural properties but need to integrate different functions to yield hybrid systems for complex operations. Typically, neither materials nor processing technologies are fully compatible with each other. The aim of the work is to combine the advantages of seemingly incompatible manufacturing processes such as high‐volume injection molding (IM) and precision additive manufacturing to produce functional and customized hybrid materials. IM is widely used for polymer processing but stands against high investment costs for tailor‐made molds with high‐resolution features. They focus on overprinting of injection‐molded parts made of thermoplastic polyurethane (TPU) with microstructures via projection‐microstereolithography (PµSL) to generate hybrid polymer materials with spatially tailored stiffness, enabling selective reinforcement, resulting in an E modulus increase of 195% compared to mere IM‐processed TPU. With that, the hybridization of processing methods is showcased to extend the product properties of polymer materials obtained via either IM or PµSL printing that have, prospectively, a maximum degree of individualization as well as a multitude of structural and functional features at the same time. To achieve optimum interfacial adhesion, the influence of surface roughness is studied, and reinforcement effects of different overprinted microstructure types are evaluated. [ABSTRACT FROM AUTHOR]

In recent years, Czochralski silicon (Cz-Si) crystals have been progressing toward n-type, large diameter and low oxygen concentration. For this purpose, the modified heating zone structure for 300 mm diameter n-type Cz-Si crystal growth with dual side-heaters has been proposed; moreover, its feasibility and effectiveness were verified through numerical simulations and on-site experiments herein. The simulation results indicate that the proposed crystal growth technique with modified parameters can effectively enhance the uniformity of longitudinal temperature gradient in the silicon melt and lower the temperature at the silica crucible bottom, for reducing the oxygen concentration at the crystal head. Based on it, 300 mm diameter n-type recharged Cz-Si (RCz-Si) crystals with an oxygen concentration in the range of 9.5–10.5 ppma were grown in on-site experiments, which is much lower than that grown in a conventional heating zone structure. More importantly, the photoluminescence (PL) images of the quarter wafers taken at the as-grown Cz-Si crystal head, middle and bottom have shown that little metastable defects can be annealed out during typical high-temperature oxidation at 1000 °C, confirming the excellent stability of thermally induced degradation. Consequently, this manuscript has demonstrated that the proposed crystal growth technique can realize dual goals of oxygen concentration control and crystal quality assurance in 300 mm diameter n-type Cz-Si crystal growth, which may promote the development of large diameter Cz-Si crystal growth techniques and the related application industries. [ABSTRACT FROM AUTHOR]

This study investigates the influence of the main process parameters of injection molding(mold temperature, melt temperature, and injection rate) on the appearance of defects of flake-pigmented metallic polymer parts. To understand the influence of process parameters, an appearance defects index (ADI) is proposed to quantify the appearance defects. In this process, we propose a criterion for judging the appearance of defects based on the results of fiber orientation and tensor distribution analyses of the skin layer, which is then verified analytically by simulating experiments from the literature. Using the Taguchi experimental method, we designed an L 25 orthogonal array to systematically evaluate the influence of process parameters. For each experimental condition, the signal-to-noise ratio (S/N ratio) was calculated to determine the optimal level of each factor and its influence on the appearance of defects. According to the results, mold temperature has the greatest influence on the appearance of defects, with an influence of 48.7%, followed by injection rate with an influence of 40.8%, and melt temperature with an influence of 10.5%. The optimal process parameters were found to be a mold temperature of 40 °C, a melt temperature of 250 °C, and an injection rate of 10 cm3/s, which resulted in a 12.6% improvement in the Appearance defects index (ADI) compared to the standard injection molding condition of ABS materials. This study confirmed that it is possible to improve the appearance of defects by adjusting the process parameters of injection molding. [ABSTRACT FROM AUTHOR]

This research investigates novel polymeric composite materials for automotive interior trim applications. The composites utilize recycled polypropylene (PPr) matrix and carboxymethylcellulose (CMC) as filler (PPr/CMC: 100/0, 95/5, and 90/10 wt.%). The materials were processed by extrusion and injection molding. Considering their intended application, the composites were evaluated for resistance to key climatic factors, i.e., temperature, humidity, and UV radiation. In addition, structural analyses and FTIR analyses were performed to assess potential heterogeneity and thermal stability. Following FTIR tests, the incorporation of carboxymethyl cellulose in polypropylene is confirmed by the detection of characteristic CMC bands for -OH, C=O, and C-O-C groups. The results indicate slight structural heterogeneity in the 5% and 10% CMC composites. However, no thermal distortions were observed in either the composites or the PPr matrix itself. The behavior of PPr/CMC composites under the action of the mentioned climatic factors has been assessed from the variation of dielectric characteristics with frequency. The strong polarization of CMC leads to a sharp increase in composites electrical conductivity after submersion in water for 480 h, suggesting weakening of the composite structure. After exposure to UV radiation, a sharp increase in conductivity is observed even after the first cycle (72 h) of UV radiation. Following the experimental results obtained in our study, it is recommended to use the PPr +10% CMC composite for obtaining different interior ornaments (carpets, supports, etc.). At the same time, the use of these materials also has the advantage of lightening the mass of the vehicle due to their lower density than polymers. [ABSTRACT FROM AUTHOR]

With the rapid development of wireless communication technologies and the miniaturization trend in the electronics industry, the reduction of electromagnetic interference has become an important issue. To solve this problem, a lot of attention has been focused on polymer composites with combined functional fillers. In this paper, we report a method for creating an acrylonitrile butadiene styrene (ABS) plastic composite with a low amount of conductive carbon and magnetic fillers preparation. Also, we investigate the mechanical, thermophysical, and electrodynamic characteristics of the resulting composites. Increasing the combined filler amount in the ABS composite from 1 to 5 wt % leads to a composite conductivity growth of almost 50 times. It is necessary to underline the temperature decrease of 5 wt % mass loss and, accordingly, the composite heat resistance reduction with an increase in the combined filler from 1 to 5 wt %, while the thermal conductivity remains almost constant. It was established that electrodynamic and physical–mechanical characteristics depend on the agglomeration of fillers. This work is expected to reveal the potential of combining commercially available fillers to construct effective materials with good electromagnetic interference (EMI) protection using mass production methods (extrusion and injection molding). [ABSTRACT FROM AUTHOR]

This paper presents the parametric investigation and optimization of various chemical treatment parameters that affect the mechanical performance of the green composite. The injection moulding method was used to produce the green composites using flax fibre (FF) and polylactic acid (PLA). The chemical parameters chosen to investigate their effects are chemical type (sodium hydroxide, sodium carbonate, and potassium hydroxide), chemical concentrations (1 %, 2 %, and 3 % (w/v)), and duration for fibre treatment (2 h, 4 h, and 6 h). The mechanical performance of the green composites was assessed by evaluating the various properties namely strength, modulus, and elongation under tensile, share, flexural, and compression loading conditions. The morphological study was also performed to examine the failure behavior of the composite after mechanical testing. The effect of fibre length (2 mm, 3 mm, 4 mm, 5 mm, and 6 mm) and fibre loading (10 wt.%, 20 wt.%, and 30 wt.%) on the performance of the flax fibre (FF)/polylactic acid (PLA) composite was also investigated. The fibre dispersion, fibre orientation, and fibre length retention were investigated to assess the characteristics of fibre during injection moulding of the developed flax fibre (FF)/polylactic acid (PLA) composite. [ABSTRACT FROM AUTHOR]

Biodegradable poly(butylene succinate‐co‐adipate)/Poly(3‐hydroxybutyrate‐co‐3‐hydoxyvalerate) (PBSA/PHBV) filled with lignocellulosic sidestream/fibers from cowpea, a neglected and underutilized African crop are produced by injection molding and extrusion film casting. Differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA) suggests that the fibers have more affinity and interfacial interaction with PBSA than PHBV. This is shown by a decrease in dampening of PBSA and an increase in dampening of PHBV with fiber addition. In addition, fiber addition results in more homogeneous crystal morphology of PBSA, while resulting in more heterogeneous crystal morphology of PHBV. The tensile strength of injection molded bio‐composites increases with fiber addition due to good interfacial adhesion between the matrix and fibers revealed by scanning electron microscope. In contrast, the tensile strength of bio‐composite films decreases with fiber addition due to the high‐volume fraction of pores in bio‐composite films that act as stress raisers. The stiffness of both injection molded, and bio‐composite films increase with fiber addition, as revealed by an increase in Young's modulus and storage modulus, while the tensile strain decreases. In conclusion, low‐value cowpea sidestream can be used as a filler to produce injection molded bio‐composites and bio‐composite films for potential application as rigid and flexible packaging. [ABSTRACT FROM AUTHOR]

Metal-polymer hybrid (MPH) injection molding is an innovative manufacturing process with vast potential in today industries. This article reviews MPH, covering its introduction, applications, significance, and associated challenges. The introduction outlines MPH unique principles distinguishing it from traditional injection molding techniques. Next, the MPH potential in the automotive industry is explored, highlighting its ability to merge high-strength metal components with polymer matrix, resulting in improved structural integrity, decreased weight, reduced gas emissions, and promising cost savings. In addition, the process allows the production of complicated shapes, providing a large design window. Furthermore, its production sustainability potential makes it an interesting alternative for eco-friendly goals. Nevertheless, several technical challenges face MPH process, which have been observed in previous research, such as process parameters, thermal expansion, shrinkage behavior, interfacial adhesion, and manufacturing defects through the molding operation are mentioned thoroughly. Furthermore, considering all the relevant factors, the future scope of study and development has also been evaluated. [ABSTRACT FROM AUTHOR]

PC/ABS blends are commonly used for the production of automotive components due to their thermal and mechanical properties. However, changes in process conditions can have a significant impact on their properties and microstructure. Therefore, determining the optimal parameters for the injection molding (IM) process is critical for effective control of the mechanical properties and quality of the injected parts. In this study, the Taguchi method is applied to investigate the relationship between the tensile stress (σ), Young's modulus (E) and IM process of PC/ABS blends. The effects of different molding parameters such as material temperature, injection pressure, holding time and mold temperature were investigated. The optimal injection parameters to achieve higher tensile stress (σ) and Young's modulus (E) were predicted by studying the signal-to-noise ratio (S/N). Thus, the objectives of the Taguchi approach for the IM process are to determine the optimal combination of process parameters and to reduce the quality variations between only a few trials. Two optimal parameter combinations were found yielding very significant mechanical properties (σ, E) of the injected parts. These optimum combinations consist of material temperature of 260 °C, injection pressure ranging between 40 and 50 bar, holding time of 8 s and mold temperature of 60 °C. Experimental results prove that injection pressure and material temperature have the most significant impact on the mechanical properties and the microstructure of PC/ABS blends. These findings may have interesting applications in the automotive industry. [ABSTRACT FROM AUTHOR]

A water-soluble binder was used to obtain TA1 sintered samples prepared by injection molding. The effects of the sintering temperature on the microstructures and mechanical properties of the sintered samples were analyzed. A relative density of >91% is achieved. Some residual carbon and oxygen remain in the sintered samples, affecting the mechanical properties. The tensile strength and elongation of the sample sintered at 1,300 °C are the highest: 592 MPa and 12.95%, respectively. Detailed electron microscopic analysis was performed to identify the morphology and nature of the resultant titanium carbides and oxides. [ABSTRACT FROM AUTHOR]

This review presents a comprehensive exploration of the advancements in polymer composites, focusing on their performance, manufacturing processes, recycling techniques, and sustainable practices. With the increasing demand for high-performance materials in various industries, including aerospace, automotive, and construction, polymer composites have emerged as a pivotal solution, offering unparalleled strength, durability, and lightweight properties. This review explores the essential characteristics of polymer composite materials and blends, highlighting the synergy between various matrices and reinforcements that lead to improved material properties. Significant emphasis is given to high-performance composites, where the integration of innovative materials and additives has led to revolutionary applications. By examining the material properties and performance, this review highlights the capabilities of polymer composites to meet rigorous requirements in special cases and extreme conditions. Furthermore, it explores the environmental impact of these materials, promoting sustainable practices throughout their lifecycle. The critical role of recycling in the manufacturing process is dissected to unveil strategies that not only mitigate environmental harm but also promote the circular economy in the composite industry. It addresses both the challenges and opportunities presented by these materials, offering insights into future directions for research and application. [ABSTRACT FROM AUTHOR]

Injection molding is one of the dominant methods for mass‐producing short fiber reinforced plastics renowned for their exceptional specific properties. In the utilization of such composite components, optimization of process parameters significantly influences material characteristics and part performance. However, in industrial practice, this process often relies on intuition and iterative experimentation. Prior studies have introduced data‐efficient optimization methods but faced limitations in adopting minor variations in the product development cycle. This study introduces a multi‐fidelity optimization framework aimed at efficiently addressing new problems by leveraging previously acquired knowledge from analogous domains, particularly accommodating alterations in material scenarios. Two data‐driven frameworks are explored: 1) Gaussian process‐based and 2) neural network‐based, each employing distinct information‐transferring techniques, hierarchical Kriging and transfer learning, respectively. Bayesian optimization of process parameters under limited data budget, which is typical in realistic industrial settings, is performed. The results highlight the efficiency of the proposed framework, demonstrating superior performance not only in data‐driven modeling but also in optimization efficiency compared to conventional single‐fidelity approaches. The Pearson correlation coefficient is utilized to assess the applicability of the multi‐fidelity framework in handling the inherent ambiguity of the similarity of problem scenarios. The proposed method is believed to be adaptable and versatile, offering potential application across various challenges in process optimization. [ABSTRACT FROM AUTHOR]

This research investigates the correlation between polymer melt viscosity, tensile properties, and injection molding energy consumption for three grades of polypropylene: a virgin grade, a recycled grade, and a modified recycled grade. Cold runner and hot runner molds are considered. The experiments focus on characterizing the thermal and mechanical energy drawn by the injection molding machine during the cycle. The data collected from the experiments are used to calculate the embodied energy as a function of the polymer viscosity and processing conditions. The analysis of the relationship between polymer rheology and processing provided guidelines for the molded parts' embodied energy and mechanical characteristics. These guidelines and estimation techniques will support sustainable design for manufacturing practices. [ABSTRACT FROM AUTHOR]

The rapid tooling of mold inserts for injection molding allows for very fast product development, as well as a highly customized design. For this, a combination of rapid prototyping methods with suitable polymer materials, like the high-performance thermoplastic polymer polyetheretherketone (PEEK), should be applied. As a drawback, a huge processing temperature beyond 400 °C is necessary for material extrusion (MEX)-based 3D printing; here, Fused Filament Fabrication (FFF) requires a more sophisticated printing parameter investigation. In this work, suitable MEX printing strategies, covering printing parameters like printing temperature and speed, for the realization of two different mold insert surface geometries were evaluated, and the resulting print quality was inspected. As a proof of concept, ceramic injection molding was used for replication. Under consideration of the two different test structures, the ceramic feedstock could be replicated successfully and to an acceptable quality without significant mold insert deterioration. [ABSTRACT FROM AUTHOR]

Micro- and nano-scale cellulosic fillers exhibit excellent dispersion and distribution within a thermoplastic matrix during the process of melt compounding or injection molding. In this study, spray-dried cellulose nanofiber (SDCNF) powders were manufactured using a pilot-scale rotating disk atomizer spray dryer. Bleached Kraft pulp (BKP), unbleached Kraft pulp (UKP), and old corrugated cardboard pulp (OCC) fibrillated at a fines level of 90% were used as feedstock materials for spray-drying. BKP-, UKP-, and OCC- SDCNFs were compounded with polypropylene using a twin screw co-rotating extruder. Maleic anhydride grafted polypropylene (MAPP) was used as a coupling agent in the composite formulations. The tensile, flexural, and impact properties of SDCNF-filled PP composites increased at 10 wt% SDCNF loading. The presence of SDCNFs in the PP matrix resulted in faster crystallization and a 12% reduction in the degree of crystallinity of the neat PP. The coefficient of thermal expansion (CTE) of neat PP was reduced by up to 31% attributable to the presence of the SDCNFs. Application of the SDCNF-reinforced PP composites in 3D printing reduced the shrinkage rate of the printed neat PP by 39%, and the printability of the PP was significantly improved with the addition of the SDCNFs. [ABSTRACT FROM AUTHOR]

The flow, level fluctuation, and initial solidification in a 1248 × 200 mm2 slab mold of stainless steel under the bifurcated SEN with diverse divergent angle, inclination angle, and immersion depth were numerically discussed and compared in this paper, and the simulation results of flow patterns and level fluctuations were validated by water model experiments. The research outcome indicated that the flow field and level fluctuation obtained through numerical simulation are generally in line with the outcomes observed in water model experiments. When the inclination angles are 0, 8, 12, and 15 deg, the level fluctuations in the mold are 8.18, 15.60, 12.19, and 11.56 mm, while the solidified shell thickness at mold outlet is 12.76, 13.08, 7.24, and 13.96 mm, respectively. When the divergent angle increases range from 0 to 15 deg, the level fluctuation in mold decreases by 5.72 mm, while the shell thicknesses at impact area and mold outlet of the narrow side increase by 3.89 and 2.87 mm, without negative adverse impact on the shell and temperature on the wide face. The SEN immersion depth has minimal infection on the level fluctuation and shell growth in the mold. As the immersion depth increases by 40 mm, the level fluctuation at the steel/slag interface and the shell thickness at the mold outlet decrease by 0.85 and 0.8 mm, respectively. The research outcomes can offer theoretical direction for optimization of level fluctuation and initial solidification behavior in stainless steel slab mold with upward bifurcated SEN. [ABSTRACT FROM AUTHOR]

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The conducted study was focused on the development of a new type of technical blend reinforced with natural fillers. The study was divided into two parts, where, in the first stage of the research, unmodified POM was reinforced with different types of natural fillers: cellulose, wood flour, and husk particles. In order to select the type of filler intended for further modification, the mechanical characteristics were assessed. The 20% wood flour (WF) filler system was selected as the reinforcement. The second stage of research involved the use of a combination of polyoxymethylene POM and poly(lactic acid) PLA. The POM/PLA blend (ratio 50/50%) was modified with an elastomeric compound (EBA) and chain extender as the compatibilized reactive (CE). The microscopic analysis revealed that for the POM/PLA system, the filler–matrix interface is characterized by better wettability, which might suggest higher adhesion. The mechanical performance revealed that for POM/PLA-based composites, the properties were very close to the results for POM-WF composites; however, there is still a significant difference in thermal resistance in favor of POM-based materials. The increase in thermomechanical properties for POM/PLA composites occurs after heat treatment. The increasing crystallinity of the PLA phase allows for a significant increase in the heat deflection temperature (HDT), even above 125 °C. [ABSTRACT FROM AUTHOR]

It is difficult to select low-cost filler materials. Specifically, carbon-based filling materials are a matter of concern, and developing a carbon-filled polymer composite with enhanced properties is necessary. In this study, the authors developed a polymer composite using virgin polypropylene (PP) as a matrix and affordable micrographite (µG) as a filler. The developed composite has many potential applications in the automotive, aerospace, and electronic industries. To prepare the test specimens, the composite was prepared using a twin-screw extruder containing 3, 6, 9, 12, or 15 wt.% µG powder (BET surface area ≈ 29 m2/g; particle size > 50 µm) followed by injection molding. Different mechanical properties like the tensile, flexural, and impact strengths were determined. The prepared composites were further characterized by means of XRD, TGA, DSC, FTIR, DMA, FESEM, and PLM tests. The results were analyzed and compared with those for PP. Improved tensile (up to ≈ 34 MPa) and flexural (up to ≈ 40 MPa) strength was observed with an increase in the µG content. However, the impact strength continuously decreased (maximum ≈ 32 J/m for PP) with fractures. These findings underscore that graphite plays a significant role in controlling the deformation behavior and ultimate strength of composites. An XRD analysis revealed that adding graphite restructured the crystalline arrangement of PP and altered the composite's crystallographic properties. Nonetheless, no induction effect (β-phase formation) was observed. A moderate enhancement in the thermal stability was observed owing to a small increase in the melt (Tm), onset (Tonset), and residual (TR) temperatures. A microstructural analysis showed that the micrographite powder strongly prevented spherulite growth and modified the graphite powder's rate of dispersion and agglomeration in a polymer matrix. The results show that graphite could be a viable low-cost alternative carbon-based filler material in polypropylene matrices. [ABSTRACT FROM AUTHOR]

This article shows three different water‐based physical blowing agents for liquid silicone rubber (LSR) in terms of physical, mechanical, and morphological properties depending on the manufacturing parameters and amounts of blowing agents. The compositions consist of common LSRs added with pure water, water–silicone oil emulsion, and aqueous silicone. The foaming process is initiated in an injection molding process. By subvolumetrically filling the mold, it is possible to foam the LSR during the injection molding process. This publication aims to compare different, water‐based blowing agents for LSR in the injection molding process. The results show that for all foams porosities between 0.25 and 0.4 are possible. An analysis of the foam structure shows that the aqueous silicone produces a significantly more homogeneous structure than the other two blowing agents. In addition, the mechanical properties are analyzed. For this purpose, tensile tests are carried out and the Shore hardness is determined. The elasticity and mechanical properties decrease slightly. The specific tensile strength also shows a small decrease, although this may be due to either the gradient of the foam structure or chemical reactions between the blowing agents and the LSR. [ABSTRACT FROM AUTHOR]

Background: Removable prostheses have seen a fundamental change recently because of advances in polymer materials, allowing improved durability and performance. Despite these advancements, notable differences still occur amongst various polymer materials and processing technologies, requiring a thorough grasp of their mechanical, physical, and therapeutic implications. The compressive strength of dentures manufactured using various technologies will be investigated. Methods: Traditional, injection molding, and additive and subtractive CAD/CAM processing techniques, all utilizing Polymethyl methacrylate (PMMA) as the main material, were used to construct complete dentures. The specimens underwent a compressive mechanical test, which reveals the differences in compressive strength. Results: All the specimens broke under the influence of a certain force, rather than yielding through flow, as is characteristic for plastic materials. For each specimen, the maximum force (N) was recorded, as well as the breaking energy. The mean force required to break the dentures for each processing technology is as follows: 4.54 kN for traditional packing-press technique, 17.92 kN for the injection molding technique, 1.51 kN for the additive CAD/CAM dentures, and 5.9 kN for the subtractive CAD/CAM dentures. Conclusions: The best results were obtained in the case of the thermoplastic injection system and the worst results were recorded in the case of 3D printed samples. Another important aspect depicted is the standard deviation for each group, which reveal a relatively unstable property for the thermoplastic injected dentures. Good results here in terms of absolute property and stability of the property can be conferred to CAD/CAM milled group. [ABSTRACT FROM AUTHOR]

Long persistent luminescence materials (LPLMs) are promising candidates for various photonic applications, owing to their ability to store light. In spite of advancements in exploring of new LPLMs, the fabrication of transparent centimeter‐sized LPLMs with pre‐designed shapes, high productivity, long afterglow multicolor luminescence, and high chemical stability, is still challenging. Here, high‐throughput manufacture of translucent crystal‐glass composites via a classical injection molding (IM) technique is demonstrated, in which persistent phosphors (PPs)‐amorphous silica nanoparticles‐polymer composites are molded into different shapes then thermally treated at elevated temperatures to obtain glass composites with embedded PP particles and customized shapes. The structural characterizations endorse that the PP particles are preserved during high temperature sintering, and the resultant crystal‐glass composites combine the unique benefits of both PPs and silica glass. Remarkably, the total production time to manufacture 100 pieces of centimeter‐sized crystal‐glass composites is 35 h, thus enabling high‐throughput production of glass composite articles by the IM method. In addition, the injection molded crystal‐glass composites demonstrate long afterglow multicolor luminescence and ultrahigh chemical durability. This study provides a massive production strategy for the fabrication of translucent and stable multicolor persistent luminescent objects with customized shapes, which can be used in numerous applications. [ABSTRACT FROM AUTHOR]

Metal sintering is a necessary step for the fabrication of metal-injection-molded parts and binder jetting techniques such as those in HP’s metal 3D printer (MetJet). This process induces significant deformations, typically ranging from 25 to 50%, depending on the porosity of the green part (printed part before post-processing). Achieving precise geometrical accuracy and consistency in the final part presents a substantial challenge to increasing the manufacturing yield. This challenge is primarily attributed to the high porosity of green parts produced by MetJet (compared with alternative technologies such as metal injection molding), which can lead to approximately 50% volumetric shrinkage after sintering. Moreover, this shrinkage is nonisotropic as it depends on nonuniform stress built up during sintering, resulting in deformations such as gravitational sag, gravitational slump, and surface drag. In this study, we employ a graph-based deep learning approach to predict the deformation of the part where deformation simulation can be substantially sped up at the voxel level. By utilizing a well-trained metal sintering inferencing engine, the final sintering deformation value can be obtained in a matter of seconds. The tested accuracy on a sample complex geometry achieves a mean deviation of 0.7 um for a 63 mm test part in a single sintering step (equivalent to 8.3 min of physical sintering time) and a mean deviation of 0.3 mm for the complete sintering cycle (~4 h of physical sintering time) [ABSTRACT FROM AUTHOR]

Highlights Textile composites are advanced materials composed of preforms combined with matrix materials. The fiber structure in the preform has a significant impact on the mechanical properties of the composite. Precise control over preform dimensions and internal fiber structural uniformity, termed ‘accurate shape control’, is essential to ensure reliable and stable composite component mechanical properties. This paper reviews current research progress on fabric deformation mechanisms, focusing on experimental characterization and numerical simulation. Experimental methods for fabric deformation include tensile, compression, bending, and shear deformation, whereas numerical methods encompass macroscopic continuum, discrete, and semi‐discrete models. The insights offered in this paper will aid a greater understanding of fabric deformation mechanisms, enabling an accurate prediction of complex shape molding and effective process parameter design, ultimately facilitating the structural design and engineering applications of textile composites. Recent trends and challenges in the study of fabric deformation mechanisms are presented. The experimental methods for fabric deformation were summarized and evaluated. Representative numerical modeling techniques and simulation methods are discussed. Some recommendations on potential future research directions are detailed. [ABSTRACT FROM AUTHOR]

This paper reports the thermally activated ultralow friction of 100% cellulose nanofiber (CNF) molding. The mechanism of friction reduction was investigated using a laboratory-built in-situ Raman tribometer. Our experimental results showed that a CNF molding exhibited an ultralow friction coefficient of below 0.04 in a CNF ring and steel disk tribopair under high-temperature conditions (T > 100°C). The results of the temperature-rise friction test showed that the friction coefficient of the CNF molding strongly depended on the temperature and decreased linearly with increasing temperature. The in situ tribo-Raman monitoring results, during friction, indicated a change in the structure of the CNF molding. Therefore, the crystallinity indices and lengths of the CNF fibers gradually changed as the temperature increased. Moreover, transfer tribofilms were observed on the counter-steel surface against the CNF rings. When the CNF molding exhibited thermally activated ultralow friction, the tribofilm was mainly composed of cellulose and graphitic carbon. Our results suggest that the thermal and friction-activated structural transformations of CNF molding and CNFderived transfer film formation are pivotal factors contributing to the ultralow friction phenomenon observed in CNF molding at high temperatures. [ABSTRACT FROM AUTHOR]

Highlights The design of composite I‐sections in aerostructures faces a significant challenge with conventional laminates because they are prone to delamination under out‐of‐plane loads. To address this issue, this study investigates the design, manufacture, and mechanical properties of 3D woven near‐net‐shaped composite I‐sections. The study also compares their advantages with equivalent laminates and examines the influence of weave patterns on their mechanical behavior. Specimens were manufactured using the vacuum‐assisted resin transfer molding technique, and quasi‐static tensile, compressive, and bending tests were conducted to assess the properties of I‐sections with three different weave patterns. It finds that the ultimate strength and damage tolerance of the considered design of 3D woven I‐sections are better than the considered design of 2D woven laminated counterparts, and different weave patterns play a significant effect in damage mode and load‐bearing capacity. In addition, using 3D woven preforms to manufacture composite I‐sections also exhibits shortened production time in terms of layup and resin infusion. The 3D woven I‐sections show improved damage tolerance over 2D counterparts. The design of weave patterns affects the properties of I‐section composites. Using 3D preforms to manufacture I‐sections exhibits shortened production time. Design consideration is proposed for the optimal weave pattern of the I‐sections. [ABSTRACT FROM AUTHOR]

Warpage deformation is a typical phenomenon for polymer injection-molded parts, mainly caused by unbalanced cooling, and it is inevitable. Complex process parameters usually lead to uncontrollable thermal behavior of the polymer materials during injection molding and significant experimental errors. This work presents an experimental mold with a flat mold cavity and nine local heating sections to determine the exact effect of temperature difference on the thermal deformation of injection molded parts. Through local heating at different positions, different warpage deformation was caused. Experimental results demonstrated the relationship between the local temperature and the local thermal warpage. The predicted results of local temperature distribution by numerical simulation presented a strong negative correlation with the experimental results (R2 = 67%); however, the warpage prediction results by numerical simulation were moderate (R2 = 35%). Machine learning with neural networks was further conducted based on the experimental results. When more data was given with a suitable neural network structure, the model prediction accuracy of warpage could be up to 97%, while for the extrapolation test, the prediction accuracy could also be up to 89%. This local thermal heating technique and neural network modeling method can be applied in further theoretical investigation of warpage of injection molded parts and support the development of new models with high accuracy in predicting warpage deformation. [ABSTRACT FROM AUTHOR]

After injection molding, plastic gears often exhibit surface defects, including those on end faces and tooth surfaces. These defects encompass a wide range of types and possess complex characteristics, which pose challenges for inspection. Current visual inspection systems for plastic gears suffer from limitations such as single-category defect inspection and low accuracy. There is an urgent industry need for a comprehensive and accurate method and system for inspecting defects on plastic gears, with improved inspection capability and higher accuracy. This paper presents an intelligent inspection algorithm network for plastic gear defects (PGD-net), which effectively captures subtle defect features at arbitrary locations on the surface compared to other models. An adaptive sample weighting method is proposed and integrated into an improved Focal-IoU loss function to address the issue of low inspection accuracy caused by imbalanced defect dataset distributions, thus enhancing the regression accuracy for difficult defect categories. CoordConv layers are incorporated into each inspection head to improve the model's generalization capability. Furthermore, a dataset of plastic gear surface defects comprising 16 types of defects is constructed, and our algorithm is trained and tested on this dataset. The PGD-net achieves a comprehensive mean average precision (mAP) value of 95.6% for the 16 defect types. Additionally, an online inspection system is developed based on the PGD-net algorithm, which can be integrated with plastic gear production lines to achieve online full inspection and automatic sorting of plastic gear defects. The entire system has been successfully applied in plastic gear production lines, conducting daily inspections of over 60,000 gears. [ABSTRACT FROM AUTHOR]