Novel Analysis Methodology of Cavity Pressure Profiles in Injection-Molding Processes Using Interpretation of Machine Learning Model

The cavity pressure profile representing the effective molding condition in a cavity is closely related to part quality. Analysis of the effect of the cavity pressure profile on quality requires prior knowledge and understanding of the injection-molding process and polymer materials. In this work, an analysis methodology to examine the effect of the cavity pressure profile on part quality is proposed. The methodology uses the interpretation of a neural network as a metamodel representing the relationship between the cavity pressure profile and the part weight as a quality index. The process state points (PSPs) extracted from the cavity pressure profile were used as the input features of the model. The overall impact of the features on the part weight and the contribution of them on a specific sample clarify the influence of the cavity pressure profile on the part weight. The effect of the process parameters on the part weight and the PSPs supported the validity of the methodology. The influential features and impacts analyzed using this methodology can be employed to set the target points and bounds of the monitoring window, and the contribution of each feature can be used to optimize the injection-molding process.

Selection Method of Molding Condition for Self-Adhesive Products Using Only Bamboo Fibers Extracted With a Machining Center Based on Bayesian Optimization

Bamboo grows naturally in Japan as an underutilized forest resource, and its fibers have high specific strength and stiffness, so much so that they are called natural glass fibers. In this study, a method for manufacturing a self-adhesive compact material by pressurizing and heating 100% bamboo fiber after extraction using a machining center, without losing the composition of bamboo, is proposed. This molded body is made of a 100% natural material and has a low environmental impact even when landfilled, contributing to the growth of bamboo for use as a raw material. In this study, the formation conditions for maximizing the tensile properties when forming platelets were investigated. First, an analysis of the variance was conducted using the orthogonal array test design to identify the factors affecting the objective variable and determine the contribution of each factor. In addition, estimates of the objective variable for the molding conditions were obtained from the Gaussian process regression model in a Bayesian optimization. Furthermore, as a result of comparing the maximum values of the properties of the molding conditions between the analysis of variance and the Gaussian process regression model, the values of the tensile properties were improved in the Gaussian process regression model.

Dielectric Spectroscopy of PP/MWCNT Nanocomposites: Relationship with Crystalline Structure and Injection Molding Condition

In this paper, we study the correlation between the dielectric behavior of polypropylene/multi-walled carbon nanotube (PP/MWCNT) nanocomposites and the morphology with regard to the crystalline structure, nanofiller dispersion and injection molding conditions. As a result, in the range of the percolation threshold the dielectric behavior shifts to a more frequency-independent behavior, as the mold temperature increases. Moreover, the position further from the gate appears as the most conductive. This effect has been associated to a modification of the morphology of the MWCNT clusters induced by both the flow of the molten polymer during the processing phase and the variation of the crystalline structure, which is increasingly constituted by γ-phase as the mold temperature increases. The obtained results allow one to understand the effect of tuning the processing condition in the frequency-dependent electrical behavior of PP/MWCNT injection-molded nanocomposites, which can be successfully exploited for an advanced process/product design.

Bond Structures between Wood Components and Citric Acid in Wood-Based Molding

Citric acid-based wood adhesive is considered a chemical-bonding wood adhesive. However, the detailed structures of the bonds between wood components and citric acid remain unknown. Here, we examine the chemical bonding structures between citric acid and wood by heteronuclear single quantum coherence-nuclear magnetic resonance (HSQC-NMR) analysis of wood-based molding using Japanese cedar (Cryptomeria japonica) and citric acid. In the HSQC-NMR spectrum of the wood molding, some esterified C/H correlation peaks appeared. The primary hydroxyl groups of polysaccharides, such as cellulose and galactoglucomannan, and the primary hydroxyl groups of the β-O-4 and β-5 substructures in lignin were found to be esterified with citric acid. In contrast, the secondary hydroxyl groups, except for xylan, barely reacted because of the steric hindrance. Additionally, the C/H correlation peak volumes of the reducing ends of mannan and xylan in the anomeric region increased after molding. It was clarified that the glycosidic bonds in the hemicelluloses were cleaved under the acidic molding condition with citric acid. The HSQC-NMR analysis revealed that the esterification of hemicellulose and lignin, and degradation of hemicellulose, proceeded under the molding condition. These results will promote understanding of the adhesive mechanism of citric acid-based wood adhesive and of the properties of the molding.

Fabrication of Carbon Fiber Reinforced Aromatic Polyamide Composites and Their Thermal Conductivities with a h-BN Filler

In this study, a carbon fiber-reinforced thermoplastic composite was fabricated using a new aromatic polyamide (APA) as a matrix. Non-isothermal crystallization behaviors in the cooling process of APA resin (a semi-crystalline polymer) and composite were analyzed by using a differential scanning calorimeter (DSC). To determine the optimum molding conditions, processing parameters such as the molding temperature and time were varied during compression molding of the Carbon/APA composite. The tensile and flexural properties and morphologies of the fabricated composites were analyzed. Molding at 270 °C and 50 MPa for 5 min. showed relatively good mechanical properties and morphologies; thus, this condition was selected as the optimal molding condition. In addition, to enhance the thermal conductivity of the Carbon/APA composite, a study was conducted to add hexagonal boron nitride (h-BN) as a filler. The surface of h-BN was oxidized to increase its miscibility in the resin, which resulted in better dispersity in the APA matrix. In conclusion, a Carbon/APA (h-BN) composite manufactured under optimal molding conditions with an APA resin containing surface-treated h-BN showed a thermal conductivity more than twice that of the case without h-BN.

Causes of the Gloss Transition Defect on High-Gloss Injection-Molded Surfaces

The gloss transition defect of injection-molded surfaces should be mitigated because it creates a poor impression of product quality. Conventional approaches for the suppression of the gloss transition defect employ a trial-and-error approach and additional equipment. The causes of the generation of a low-gloss polymer surface and the surface change during the molding process have not been systematically analyzed. This article proposes the causes of the generation of a low-gloss polymer surface and the occurrence of gloss transition according to the molding condition. The changes in the polymer surface and gloss were analyzed using gloss and topography measurements. The shrinkage of the polymer surface generates a rough topography and low glossiness. Replication to the smooth mold surface compensates for the effect of surface shrinkage and increases the surface gloss. The surface stiffness and melt pressure influence the degree of mold surface replication. The flow front speed and mold temperature are the main factors influencing the surface gloss because they affect the development rate of the melt pressure and the recovery rate of the surface stiffness. Therefore, the mold design and process condition should be optimized to enhance the uniformity of the flow front speed and mold temperature.

Experimental and Analytical Resin Impregnation Characterization in Carbon Fiber Reinforced Thermoplastic Composites

Effect of molding condition on resin impregnation behavior and the associated mechanical properties were investigated for carbon fabric reinforced thermoplastic composites. Carbon fiber yarn (TORAYCA, Toray) was used as a reinforcement, and thermoplastic PI (AURUM PL 450 C, Mitsui Chemicals) was used as the matrix. CFRTP textile composites were compression-molded with a hot press system under the molding temperature, 390 °C, 410 °C and 430 °C, molding pressure 2 MPa and 4 MPa and molding time 0∼300 s. In order to evaluate the impregnated state, cross sectional observation was performed with an optical microscope. Specimen cross-section was polished and finished with alumina slurry for a clear observation. The images observed were processed through image processing software to obtained impregnation ratio which defined as the resin impregnation area to the cross-sectional area of a fiber yarn. Resin impregnation was accelerated with molding temperature and pressure. At molding temperature more than 410 °C, resin impregnation was similar irrespective of temperature. Tensile test results indicated that modulus and strength increased with resin impregnation. Resin impregnation during molding was predicted using the analytical model based on Darcy’s law and continuity condition. The analysis could successfully predict the impregnation behavior despite the difference in molding pressure and temperature.