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We examine the effects of different process parameter settings on variations in melt-filling pressure, viscosity index, and part weight based on the use of real-time pressure sensor readings of the inside of the injection melt flow path. In the experiment, widely used polypropylene materials and round-shaped molded parts are selected as the molding and study object. At the same time, pressure sensors are used at different positions to perform data acquisition to enable research into the variation process of the melt-filling pressure, allowing for a viscosity index equation to simultaneously calculate viscosity indexes and observe weight variations in the samples. The obtained data will be a basis for setting up smart manufacturing in the future. The research showed the following: (i) the installation of the real-time pressure sensing modules allowed the variation process of the melt-filling pressure to be monitored along a path from the injection barrel to the mold cavity; (ii) the viscosity index was subject to changing the melt temperature, the injection speed, and the V/P switch-over point of the screw; and (iii) the melt temperature change had a considerable impact on part weight and changes in the injection speed had a relatively significant impact on viscosity variation.

Fiber-reinforced thermoplastic components are widely used in the automotive industry and are generally fabricated using injection molding. The mechanical properties of such components are critically dependent on the length and orientation of the fibers in the molded product. In this study, a plate with both transverse and longitudinal ribs across the entire surface is designed based on the concepts of the oil pan of vehicles. The novel injection molding machine is developed to have the capability to injection molding long-fiber-reinforced thermoplastic and maintain fiber length during the molding process. The study especially emphasizes the effects of back pressure, rib thickness, and plate thickness. The results show that the fiber length increases with a decreasing back pressure and an increasing plate thickness and rib thickness. The effect of the plate thickness on the fiber length is particularly significant. Moreover, the fiber orientation of the long-side and short-side rib is more in the flow direction.

Injection molding is a cyclic process of producing plastics products by injecting molten plastic materials. There is much complexity in the process because it is a highly non-linear process; many factors affect the product quality after long-run fabrication processes. In this study, product weight is defined as product quality, and this research aims to minimize the variation in the product weight. In this study, a standard process parameter setup procedure is proposed in order to set the process parameters in a close to optimized value based on the information collected by the sensors so the adaptive process control system can work well. Three polypropylene materials with low to high MI (melting index) values were used to verify the adaptive control system. The study with the information collected through two sensors installed in the machine—the injection nozzle pressure sensor and tie-bar strain gauge. Based on a series of results in the preliminary experiments, the appropriate V/P switchover point and clamping force could be judged from the peak pressure and clamping force peak for materials with different viscosities, respectively. The viscosity index and peak pressure strongly correlated with the weight of the injection molded parts toward the materials of different viscosity. The viscosity index, peak pressure, and clamping force peak are defined in this research as the quality monitoring characteristics used to guide the adjustment and increase the stability of the process in the presented control system. The experiment reveals that a combination of nozzle pressure curve-based adaptive process control incorporated with clamping force peak monitoring can decrease the weight variation of the injection molded parts. With this system, the coefficient of variation of product weight (Cv) of different viscosity materials from low to high can be decreased to 0.031%, 0.020%, and 0.024%, respectively.

To increase the productivity of injection molding machines, we developed a smart injection part weight stability control system based on C++ programming and domain knowledge. The proposed system is meant to eliminate variability in the quality of injected parts by adjusting the changeover position. We developed a viscosity index based on melt pressure data related to guide the adjustment to the changeover position in accordance with material properties. This was achieved by mounting a pressure sensor on the nozzle of the injection molding machine to enable the on-line monitoring of pressure throughout the injection molding process. A series of experiments was conducted to characterize the relationship between viscosity index and injection-molded samples in order to validate the efficacy of the proposed injection stability system. Single-factor experiments were conducted with the changeover position and melt temperature as parameters. The quality of the molded samples obtained under different process parameters was evaluated in terms of weight. Experiment results revealed a correlation between changes in viscosity index and changes in the weight of the samples. The injection stability system can also be operated in self-adjusting mode, in which the changeover position is varied according to viscosity index. In experiments, abnormal machine operations prompted the adjustment of changeover position. Variation in the weight of parts was used to define an index to validate the efficacy of the proposed system.

Scientific injection molding technologies involve the integration and collaboration of cyber-physical systems and smart manufacturing. In order to achieve adaptive process control and production optimization, injection molding systems with real-time sensing have gradually become the development- and application-trend of smart injection molding. At the same time, this technology is a highly non-linear process in which many factors affect the product quality during long-run fabrication processes. Therefore, in order to grasp changes in the characteristics of plastic materials and product quality monitoring, the injection process has become an important research topic. We installed sensors in the molding machine (injection barrel, nozzle, and mold-cavity) to collect the melting pressure and used different materials (semi-crystalline and amorphous polymer; the melting-fill-index (MFI) is unified to 14.5 ± 0.5 g/10 min) to explore the influences of melting pressure variation and its viscosity index on the quality characteristics of molded products. The experiment reveals that a combination of barrel, nozzle, and mold-cavity sensing on the melt-pressure trend-based injection process-control incorporated with viscosity index monitoring can confirm the weight and shrinkage variation of the injection product. At the same time, the pressure and viscosity index value measured and calculated during the melt-filling of two materials with similar MI resulted in significant variations in the amorphous polymer. This study showed the possibility of mastering and controlling the rheology (barrel position) and shrinkage properties of polymers and successful application in various product-quality monitoring platforms.

It is known that the weldline reduces the mechanical strength of the conventional injection molded parts. Systematic studies on the weldline strength of thin-wall molded parts were not yet reported. This study investigates the effect of processing conditions including melt temperature, mold temperature, injection speed and packing pressure on the weldline strength of thin-wall parts. Tensile test specimen of 2.5, 1 and 0.8 mm thick were injection molded under specified conditions. Both single gate and double gates were used to form parts with and without weldlines. Part tensile strengths were measured experimentally. From the experimental results, it was found that higher melt temperature and mold temperature as well as faster injection speed will increase weldline strength whereas higher packing pressure would decrease weldline strength. Melt temperature and mold temperature are two parameters that affect weldline strength most significantly within the current molding window. Higher melt and mold temperatures not only lower the residual stress but also help the diffusion of molecular chains leading to a higher degree of bonding at the weldline interface. On the other hand, high packing pressure leads to higher residual stress formation and reduces the molecular bonding rate. Part thickness also exhibits significant effect on weldline strength reduction. Thinner parts resulting in higher percentage of frozen layer in filling process thus limit the bonding rate at weldline interface. From the regression analysis, the KIM model with corrected terms in the fitting coefficient was found to correlate process conditions and weldline strength reduction quite well. [ABSTRACT FROM AUTHOR]

Effect of processing conditions including injection speed, melt temperature, mold temperature and packing pressure on tensile properties of polycarbonate (PC) thin-wall parts were investigated. Tensile test specimen with thickness of 2.5, 1.0 and 0.8 mm were injection molded under specified conditions. Tensile properties and residual stresses were measured experimentally. It was found that the residual stress plays a more significant role in influencing part tensile properties than flow-induced molecular orientation. Part thickness and injection speed are two key factors that affect residual stress most significantly within the current molding window. As part thickness decreases, residual stress increases resulting in the greater influence in reduction of part tensile strength, yield stress as well as Young's modulus. Higher melt temperature and higher mold temperature would reduce residual stress whereas higher injection speed and higher packing pressure would increase residual stress. Associated with the decrease of residual stress, part's tensile strength, yield strength and Young's modulus increase with increased melt temperature, mold temperature and injection speed. On the other hand, higher packing pressure results in a decrease of part mechanical strength. [ABSTRACT FROM AUTHOR]