Injection-molded Parts Research Articles

Research on injection molded parts defect detection algorithm based on multiplicative feature fusion and improved attention mechanism

Injection molded parts are increasingly utilized across various industries due to their cost-effectiveness, lightweight nature, and durability. However, traditional defect detection methods for these parts often rely on manual visual inspection, which is inefficient, expensive, and prone to errors. To enhance the accuracy of defect detection in injection molded parts, a new method called MRB-YOLO, based on the YOLOv8 model, has been proposed. This method introduces several key improvements: (1) the MAFHead, a four-detection head based on multiplicative feature fusion, which replaces the original detection head to enhance feature representation; (2) the RepGFPN-SE module, a re-parameterized generalized feature pyramid network that improves detection of small objects by replacing the original C2f. module; (3) and the BiNorma module, employing a bi-level routing attention mechanism to optimize the training process by reducing input distribution changes across layers. The effectiveness of the MRB-YOLO model was validated through ablation and contrast experiments using a specially constructed dataset of injection molded parts defects. The results demonstrated an accuracy of 88.8%, a recall rate of 86.8%, and a mean average precision (mAP) of 91.5%. Compared to the YOLOv8n model, the MRB-YOLO model shows an increase in accuracy by 8.2%, in recall rate by 17.2%, and in mAP by 11.8%. These findings confirm that the MRB-YOLO model meets the requirements for accurate detection of defects in injection molded parts.

Numerical Simulation of Microcellular Injection Molding: A Case Study

The microcellular injection molding, often referred to as MuCell®, is an innovative polymer processing technique that utilizes supercritical inert gases, such as CO2 or N2, to manufacture lightweight plastic products. This technology has gained significant attention in recent years due to environmental concerns and the increasing demand for lightweight components with superior mechanical properties. However, challenges related to surface finish quality and limited mechanical properties have impeded its widespread adoption. This paper provides a comprehensive overview of the microcellular injection molding process. To evaluate the practicality of the MuCell® process, an industrial case study is conducted, assessing its production reliability and overall product quality. A comparative rheological analysis is performed to discern the distinctions between MuCell® and traditional injection molding, thus validating the claimed advantages of microcellular injection. Based on the accrued findings, it is deduced that MuCell® proves to be a pertinent injection molding technique for fabricating lightweight plastic components featuring enhanced dimensional stability, reduced shrinkage, and minimized warping when compared to conventionally injection-molded parts.

Fused Filament Fabrication of Slow-Crystallizing Polyaryletherketones: Crystallinity and Mechanical Properties Linked to Processing and Post-Treatment Parameters.

Recent advancements in thermoplastics within the polyaryletherketone (PAEK) family have enhanced additive manufacturing (AM) potential in fields like aerospace and defense. Polyetheretherketone (PEEK), the best-studied PAEK, faces limitations in AM due to its fast crystallization, which causes poor inter-filament bonding and warping. This study investigated alternative, slow-crystallizing PAEK polymers: polyetherketoneketone (PEKK-A) and AM-200, a PEEK-based copolymer. Both can be printed in an amorphous state and then annealed to improve crystallinity and mechanical properties. Despite their potential, these materials have been minimally explored for AM. Our analysis compared the mechanical performance of as-printed and annealed samples and showed that slow-crystallizing PAEKs outperform fast-crystallizing PEEK. As-printed PEKK-A and AM-200 parts reached tensile strengths of 69 MPa and 47 MPa, respectively, which are about 80% of the values for injection-molded parts. In contrast, PEEK achieves only 25% due to poor inter-layer bonding. Annealing increased crystallinity (15.7% for PEKK-A, 19% for AM-200), simultaneously leading to a coalescence of smaller pores into larger ones, which affected mechanical integrity. Annealing strengthened the printed filament direction, while Z-direction strength remained limited by interlayer adhesion. Our work provides new insights into optimizing these relationships to expand the applicability of PAEK in additive manufacturing.

Inclusion Detection in Injection-Molded Parts with the Use of Edge Masking.

The algorithm and prototype presented in the article are part of a quality control system for plastic objects coming from injection-molding machines. Some objects contain a flaw called inclusion, which is usually observed as a local discoloration and disqualifies the object. The objects have complex, irregular geometry with many edges. This makes inclusion detection difficult, because local changes in the image at inclusions are much less significant than grayscale changes at the edges. In order to exclude edges from calculations, the presented method first classifies the object and then matches it with the corresponding mask of edges, which is prepared off-line and stored in the database. Inclusions are detected based on the analysis of local variations in the surface grayscale in the unmasked part of the image under inspection. Experiments were performed on real objects rejected from production by human quality controllers. The proposed approach allows tuning the algorithm to achieve very high sensitivity without false detections at edges. Based on input from the controllers, the algorithm was tuned to detect all the inclusions. At 100% recall, 87% precision was achieved, which is acceptable for industrial applications.

CNCR-YOLO: A Comprehensive Optimization Strategy for Small-Target Defect Detection in Injection-Molded Parts

CNCR-YOLO: A Comprehensive Optimization Strategy for Small-Target Defect Detection in Injection-Molded Parts

Effect of Films on In‐Mold Decoration and Microcellular Foaming Injection Molding Parts: Cell Structure, Surface, Warpage, and Mechanical Properties

ABSTRACTThe in‐mold decoration and microcellular foaming injection molding (IMD‐MIM) process was proposed to solve the apparent quality problem of polypropylene in microcellular foaming injection molding. Based on physical experiments and finite element simulation, stainless steel (ST) and polyethylene glycol terephthalate (PET) decorative films were selected for analysis, and the influence of the type and thickness of the decorative films on the cell structure, surface morphology, warpage deformation, and mechanical properties was revealed. The results show that the surface quality of the samples coated is significantly improved, and the asymmetric temperature field caused by the films changes the structure and distribution of the cells. The cell density on the coated side is higher than that on the non‐coated side, and the average cell diameter is smaller, and the foam core layer is shifted to the coated side. The warpage caused by ST film is larger, up to 2.836 mm. With the intervention of ST film and PET film, the impact properties of the samples have little change, but the tensile and flexural properties of the foamed samples have been effectively improved. The tensile strength increased by 28.6% and 25.9%, while the flexural strength increased by 28.6% and 28.1%, respectively. This study provides new insights into the comprehensive optimization of the structure and performance of polypropylene microcellular foaming materials and provides support for the development and application of lightweight materials in the future.

Facilitating the Production of 3D-Printed Spare Parts in the Design of Plastic Parts: A Design Requirement Review

Using additive manufacturing for spare part production can ensure that spare parts are available for a long time. However, spare parts are currently not designed for additive manufacturing. This study aimed to find how the production of 3D-printed spare parts can be facilitated in the design of plastic parts. We used a literature review and illustrative case to find how the design requirements for standard injection moulded plastic parts relate to the manufacturing capabilities of additive manufacturing for spare parts. The design requirements were defined by assigning corresponding structural and material properties. These requirements were then used to construct and evaluate the capabilities of additive manufacturing compared to injection moulding. It was found that additive manufacturing is especially suitable for requirements like Accuracy, Heat resistance, and Chemical resistance. However, to fully enable 3D-printed spare parts, certain design challenges still need to be tackled. Designers should pay careful attention to the synergies and trade-offs between design requirements and the challenges that might arise from the combination of certain requirements. Also, designers should ensure products are easily reparable before considering 3D-printed spare parts. If we target these challenges in the design phase, we can facilitate 3D-printed spare parts that enable product repairability.

An artifactual fibre overlap removal algorithm for micro-computed tomography image post-processing and 3D microstructure generation with graphics processing unit acceleration

A novel algorithm based on radial basis functions is proposed for the removal of artifactual fibre overlap within fibre structures extracted from micro-computed tomography (micro-CT) images of fibre reinforced polymer matrix composites. The proposed algorithm is highly efficient and excels in preserving the original fibre structures extracted from the micro-CT images. Besides, graphics processing unit (GPU) acceleration is applied to further enhance the efficiency of the fibre overlap removal process. Furthermore, the proposed algorithm is also modified for the generation of periodic 3D microstructures. For practical application, the proposed algorithm is implemented for both the artifactual fibre overlap removal within micro-CT images from an injection moulded part and the microstructure generation for 3D printed samples. The unidirectional elastic modulus of the resultant microstructures is computed via numerical simulations and shows a close match to the experimental measurements with relative errors less than 2%. Overall, the proposed algorithm significantly facilitates the reconstruction of micro-CT image-based numerical models and can also be easily repurposed to generate complex microstructures, which is of great value for the development of data-driven models for characterization and design of composite materials that demands large amounts of data on material microstructures.

Influence of Processing Parameters in Injection Molding on the Properties of Short Carbon and Glass Fiber Reinforced Polypropylene Composites

Short-fiber reinforcement is a potent approach to improving the material properties of injection-molded parts. The main consideration in such reinforced materials is to preserve the fiber length, as this is the major influence on the properties of a given composite. The aim of this work was to investigate the different influencing parameters in injection molding processing on the properties of short carbon and glass fiber-reinforced polypropylene. We investigated parameters like melt temperature and back pressure, but also machine size and pre-heating regarding their influence on the tensile properties. We found that adjustments of melt temperature and back pressure only yield small improvements in the fiber length and the tensile properties, also depending on machine size, but a pre-heating step of the granules can significantly improve the properties.

High-Quality Foaming and Weight Reduction in Microcellular-Injection-Molded Polycarbonate Using Supercritical Fluid Carbon Dioxide under Gas Counter Pressure.

Microcellular injection molding (MuCell®) using supercritical fluid (SCF) as a foaming agent to achieve weight reduction has become popular in carbon emission reduction. In the typical MuCell® process, SCF N2 is commonly used. Although SCF CO2 exhibits high solubility and can achieve a high weight reduction, controlling the foaming is not easy, and its foaming cells are usually larger and less uniform, which limits its industrial application. Our previous studies have shown that gas counter pressure (GCP) can improve the foaming quality effectively. Here, we investigated whether or not the CO2 SCF foaming quality could be improved, and weight reduction was achieved for polycarbonate (PC) material. This is quite important for the electronics industry, in which most of the housing for devices is made of PC materials. MuCell® was subjected to molding experiments using the parameters of the SCF dosage, melt temperature, mold temperature, and injection speed. The results revealed that using CO2 gas for the PC material can reduce the size of microcellular cells to 40 µm and increase the cell densities to 3.97 × 106 cells/cm3. Using GCP significantly improved the microcellular injection-molded parts by reducing the cell size to 20.9 µm (a 45.41% improvement) and increasing the cell density to 8.04 × 106 cells/cm3 (a 102.48% improvement). However, implementing GCP may slightly decrease the target weight reduction. This study reveals that microcellular injection molding of PC parts using SCF CO2 can achieve high-quality foaming and reduce the weight by about 30%.

Calculation of the bonding strength of semi-crystalline polymers during overmolding

Injection molding is widely used in the plastics manufacturing industry. However, there is a need to better understand and calculate the bonding strength between the injection-molded part and the insert, especially for semi-crystalline polymers. The weldability of semi-crystalline polymers differs from that of amorphous polymers. Semi-crystalline polymers cannot heal until they reach their glass transition temperature, unlike amorphous polymers, as the crystalline particles prevent molecule motion below this temperature. To account for this difference, we have developed a method that takes into effect the crystalline parts of semi-crystalline polymers in the calculation of healing. We used polypropylene (PP) in our experiments, and calculated healing with a new method based on the method we previously described for the healing of amorphous polymers.

Tribology Behavior of In-Situ FDM 3D Printed Glass Fibre-Reinforced Thermoplastic Composites

Fused deposition modeling (FDM) 3D-printed parts are generally weaker compared to injection-moulded parts. Fibre reinforcement is one of the techniques used to enhance the mechanical strength and the tribological behavior of the FDM-printed parts. Recently, a new method for creating FDM 3D-printed composites was developed. Current work focuses on the tribological behavior of the glass fibre-reinforced PLA, manufactured using this new composite manufacturing method. Experiments were conducted to investigate the effect of Glass Fibre (GF) reinforcement on FDM 3D-printed thermoplastic composites, specifically polylactic acid (PLA) under different linear sliding speed and directions. All 3D printed glass fibre-reinforced PLA (PLA-GF) composites exhibited a lower wear rate and a higher friction coefficient compared to 3D printed PLA. Increasing in disc’s linear speed or sliding speed of the pins resulted in a lower coefficient of friction and wear rate. In addition, a perpendicular raster direction towards the disc rotation or pin motion experienced greater friction and greater wear.

Supplementary treatment of FDM printed parts. Review

The application of additive technologies to the manufacture of polymer and composite products is now actively expanding. The FDM printing process is popular because of its ability to adapt to specific tasks and to bring products with complex geometries into production quickly and at minimal cost, and is seen as a technology that can compete with injection molding. However, due to the nature of the process, FDM printed parts are significantly inferior in quality to injection molded parts. Much attention is now being paid to research into supplementary treatment methods to improve the properties of FDM printing parts. However, there is no complete and clear description of such methods, nor are there any recommendations on the choice of treatment methods aimed at improving the specific parts properties. The aim of this review is to analyse the research in the field of post-treatment of parts in order to systematise their advantages and limitations, which will allow a more reasoned choice of a post-treatment method to improve specific properties of FDM printing parts. <br> The bibliography includes 120 references.

Comparison of Hybrid Machine Learning Approaches for Surrogate Modeling Part Shrinkage in Injection Molding.

Machine learning (ML) methods present a valuable opportunity for modeling the non-linear behavior of the injection molding process. They have the potential to predict how various process and material parameters affect the quality of the resulting parts. However, the dynamic nature of the injection molding process and the challenges associated with collecting process data remain significant obstacles for the application of ML methods. To address this, within this study, hybrid approaches are compared that combine process data with additional process knowledge, such as constitutive equations and high-fidelity numerical simulations. The hybrid modeling approaches include feature learning, fine-tuning, delta-modeling, preprocessing, and using physical constraints, as well as combinations of the individual approaches. To train and validate the hybrid models, both the experimental and simulated shrinkage data of an injection-molded part are utilized. While all hybrid approaches outperform the purely data-based model, the fine-tuning approach yields the best result in the simulation setting. The combination of calibrating a physical model (feature learning) and incorporating it implicitly into the training process (physical constraints) outperforms the other approaches in the experimental setting.

Non-isothermal crystallization kinetics of biocomposites based on PLA/PHBV and spent coffee grounds

AbstractThis study deals with the modification of a predominantly amorphous poly(lactic acid) (PLA) by blending it with a semi-crystalline biopolymer, polyhydroxybutyrate-co-valerate (PHBV), which has a high crystallinity. The blends with different concentrations of PLA and PHBV were compounded with spent coffee grounds (SCGs) and processed by injection moulding. The structural, thermal and mechanical properties of the produced samples were investigated. Particular attention was paid to the effect of the presence of SCG and the concentration of PHBV in the blend on the crystallization kinetics and the heat deflection temperature (HDT). For equimolar blends, only a slight increase in HDT (about 5 °C) was observed, but the addition of PHBV suppressed the cold crystallization of PLA, which otherwise negatively affects the dimensional stability of injection moulded parts. A similar effect, but to a lesser extent, was achieved by adding SCG to the PLA matrix. Thus, it is clear that the material structures of PLA/PHBV blends and composites help to minimize additional shrinkage of the parts and increase their dimensional stability. Due to the co-continuous structure of the symmetric PLA/PHBV blends and the increase in the degree of crystallinity from 36 to 47% by annealing the produced samples, the heat deflection temperature increased from 65 up to 90 °C.

Influence of inlay consolidation quality on morphology of hybrid injection-moulded parts and their bending behaviour

Influence of inlay consolidation quality on morphology of hybrid injection-moulded parts and their bending behaviour

Optimization Strategy for Process Design in Rubber Injection Molding: A Simulation-Based Approach Allowing for the Prediction of Mechanical Properties of Vulcanizates.

Selecting the optimal settings for the production of rubber goods can be a very time-consuming and resource-intensive process. A promising method for optimizing rubber processing in a short period of time is the use of simulation routines. However, process simulations have only recently enabled meaningful predictions of not only the part's state of cure but also its mechanical characteristics. As a first approach, second-order polynomials were considered suitable for describing the properties of compression-molded parts. However, more precision is required for injection molding due to the narrower distribution of mechanical characteristics of parts produced at different vulcanization temperatures. This became evident when the approximation of mechanical data with second order models partly revealed significant failures of part behavior prediction. To tackle this issue, a combined approach for approximation is proposed in this contribution by means of logistic growth function in addition to second order polynomials. To feed the model, an experimental plan was designed for producing injection-molded parts from an SBR compound at various temperatures and to different degrees of cure. The parts obtained were then characterized mechanically, and the results were opposed to varying degrees of cure and extents of reaction to calculate the model coefficients. Once available, a simulation-based calculation of the mechanical part quality is possible. The comparison of test results from the simulation and the real process has shown a reliable prediction, as simulation results were found within the natural deviation of the real measurements.

Injection Moulded Part Analysis by Alignment of Simulated and Referent Part Geometry

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.

A comparison of additive manufactured to injection molded Martian regolith based polymer matrix composites

The completed study investigated the creation of Martian regolith simulant composite parts using injection molding and additive manufacturing. Traditional manufacturing techniques such as injection molding are not feasible on the Martian surface therefore in-situ processes must be developed using additive manufacturing processes to prepare habitats prior to having a human presence on the surface. The goal of this study was to investigate the impacts of additive manufacturing on the material property values between parts made using traditional injection molding and additive manufacturing. Martian regolith simulant composite pellets were created by combining a Martian regolith simulant at 40 wt% loading with polypropylene via twin screw extrusion. This material was then used to create test specimens using injection molding and additive manufacturing. Samples underwent tensile, flexural, Izod impact, and immersion density tests according to ASTM International and standardized test instructions. Additive manufactured parts saw a nearly 40% reduction in tensile and flexural strength with more than double the tensile modulus when compared to injection molded parts. The flexural modulus for additive manufacturing was around 36% that of the injection molded part with a minor decrease in density of around 13%. The collected test results suggested that while there were differences in the material property values between the manufacturing processes, a more interesting foaming behavior of the extrudite was observed during the additive manufacturing process resulting in an extremely rough and pitted surface. This rough surface finish was a stark comparison to the smooth injection molded parts. This observed foaming behavior in the polymeric composite material during thermal processing prompted the theory that thermal releases from the Martian regolith simulant was the most likely cause of the observed differences. Pellet surface moisture tests, Martian regolith simulant thermogravimetric analyses, and literature reviews of thermal decomposition of the Martian regolith simulant constituents revealed that most likely olivine releases oxygen and hydrated silica releases water during the thermal processing of the Martian regolith simulant composite. During a closed mold process such as injection molding, these volatile gases are forced out of the part by the pressures of the molding process, but in an open to atmosphere process such as additive manufacturing these gases foam to the surface during cooling leaving the part with an inferior surface finish.

Cross-machine predictions of the quality of injection-molded parts by combining machine learning, quality indices, and a transfer model

Cross-machine predictions of the quality of injection-molded parts by combining machine learning, quality indices, and a transfer model