The current study presents an investigation on the optimization of injection molding parameters of HDPE/TiO₂ nanocomposites using grey relational analysis with the Taguchi method. Four control ...factors, including filler concentration (i.e., TiO₂), barrel temperature, residence time and holding time, were chosen at three different levels of each. Mechanical properties, such as yield strength, Young's modulus and elongation, were selected as the performance targets. Nine experimental runs were carried out based on the Taguchi L₉ orthogonal array, and the data were processed according to the grey relational steps. The optimal process parameters were found based on the average responses of the grey relational grades, and the ideal operating conditions were found to be a filler concentration of 5 wt % TiO₂, a barrel temperature of 225 °C, a residence time of 30 min and a holding time of 20 s. Moreover, analysis of variance (ANOVA) has also been applied to identify the most significant factor, and the percentage of TiO₂ nanoparticles was found to have the most significant effect on the properties of the HDPE/TiO₂ nanocomposites fabricated through the injection molding process.
In recent years, the development and use of polymeric nanocomposites in creating advanced materials has expanded exponentially. A substantial amount of research has been done in order to design ...polymeric nanocomposites in a safe and efficient manner. In the present study, the impact of processing parameters, such as, barrel temperature, and residence time on the mechanical and thermal properties of high density polyethylene (HDPE)-TiO₂ nanocomposites were investigated. Additionally, scanning electron microscopy and X-ray diffraction spectroscopy were used to analyze the dispersion, location, and phase morphology of TiO₂ on the HDPE matrix. Mechanical tests revealed that tensile strength of the fabricated HDPE-TiO₂ nanocomposites ranged between 22.53 and 26.30 MPa, while the Young's modulus showed a consistent increase as the barrel temperature increased from 150 °C to 300 °C. Moreover, the thermal stability decreased as the barrel temperature increased.
Thermoplastics injection molding is a manufacturing process used for mass-production of plastic parts. The process includes four main stages during which material used goes through complicated ...thermo-mechanical changes. In order to make the process more controllable and repeatable it is, at first, necessary to understand which parameters are the most important ones. The following paper describes how application of statistical feature selection methods, such as Information gain and ReliefF, allows to identify which injection molding parameters have a greater influence on the final part quality. The article gives short description of the above-mentioned methods and shows what were results of their application on dataset obtained from 160 machine runs, during which 41 machine and process parameters were logged.
Due to the fact that different injection molding conditions tailor the mechanical response of the thermoplastic material, such effect must be considered earlier in the product development process. ...The existing approaches implemented in different commercial software solutions are very limited in their capabilities to estimate the influence of processing conditions on the mechanical properties. Thus, the accuracy of predictive simulations could be improved. In this study, we demonstrate how to establish straightforward processing-impact property relationships of talc-filled injection-molded polypropylene disc-shaped parts by assessing the thermomechanical environment (TME). To investigate the relationship between impact properties and the key operative variables (flow rate, melt and mold temperature, and holding pressure), the design of experiments approach was applied to systematically vary the TME of molded samples. The TME is characterized on computer flow simulation outputs and defined by two thermomechanical indices (TMI): the cooling index (CI; associated to the core features) and the thermo-stress index (TSI; related to the skin features). The TMI methodology coupled to an integrated simulation program has been developed as a tool to predict the impact response. The dynamic impact properties (peak force, peak energy, and puncture energy) were evaluated using instrumented falling weight impact tests and were all found to be similarly affected by the imposed TME. The most important molding parameters affecting the impact properties were found to be the processing temperatures (melt and mold). CI revealed greater importance for the impact response than TSI. The developed integrative tool provided truthful predictions for the envisaged impact properties.
This paper reports on the influence of injection molding parameters and environmental testing on the permittivity of different thermoplastic materials used in MID technology. Permittivity and ...dielectric loss angle measurements up to frequencies of 3 GHz were performed by using suitable resonator structures on flat test substrates fabricated by LPKF-LDS ® technology. It was found that the permittivity of LCP is only negligibly affected by injection molding parameters. Furthermore, during environmental tests the best performance was observed for LCP.
The objective of the new method is to develop an innovative multicomponent moulding with one die, which is specially applicable in automobile industry. The new concept multi component moulding system ...of this research is the secondary cavity for secondary material which is formed by the moving of the core. Recently, this method has faced with problem of flash, short shot in filling and also gluing when manufacturing multi component of car door-trim with electrical core-back coinjection machine.Process parameters, material and injection die which consist lots of parameters such as injection pressure, ram speed, mold-melt temperature, core back distance, viscosity of material and so on are considered to solve problem of new technique. The methodology combines the use of the design of experiment (DOE) and CAE flow simulation software, to reduce the injection molding parameters and to predict the role of parameters on process of manufacturing. We simulate the process with models of the three-dimensional geometry of the multicomponent moulding, which have a minimum distance of core back of 1.5 mm(second component), and study the variation of different process parameters as this core back increased. From the CAE analysis, the optimum process parameters are obtained with the optimal distance of core back of 2.0 mm. Successive processes for moulding car door-trim multi component in practical experiments explain for the good accuracy of the methodology and the efficiency of the proposed optimization parameters.
Micro weld lines are the common problem that occurs for plastic molded parts through injection molding process. This study focus on the formation of weld lines of molten polypropylene and ...polypropylene-glass-fiber reinforced composite under different parameters (melt temperature, material & mold design). Three different mold with different design were fabricated and injected with molten polypropylene and polypropylene-glass-fiber reinforced. The experimental result of the length, angle and location of the weld line were compared to the result from Autodesk Simulation Moldflow Adviser software. The result show a good resemblance with polypropylene with melt temperature 240oC and polypropylene-glass-fiber reinforced (10, 20, 25%) but not with polypropylene with melt temperature 250oC and 260oC. It is also concluded that the melt temperature, type of material and mold design affects the formation of weld lines.
The objective of this study is to propose an intelligent methodology for efficiently optimizing the injection molding parameters when multiple constraints and multiple objectives are involved. ...Multiple objective functions reflecting the product quality, manufacturing cost and molding efficiency were constructed for the optimization model of injection molding parameters while multiple constraint functions reflecting the requirements of clients and the restrictions in the capacity of injection molding machines were established as well. A novel methodology integrating variable complexity methods (VCMs), constrained non-dominated sorted genetic algorithm (CNSGA), back propagation neural networks (BPNNs) and Moldflow analyses was put forward to locate the Pareto optimal solutions to the constrained multiobjective optimization problem. The VCMs enabled both the knowledge-based simplification of the optimization model and the variable-precision flow analyses of different injection molding parameter schemes. The Moldflow analyses were applied to collect the precise sample data for developing BPNNs and to fine-tune the Pareto-optimal solutions after the CNSGA-based optimization while the approximate BPNNs were utilized to efficiently compute the fitness of every individual during the evolution of CNSGA. The case study of optimizing the mold and process parameters for manufacturing mice with a compound-cavity mold demonstrated the feasibility and intelligence of proposed methodology.
Based on the grey relational analysis, this work proposes an effective approach for optimizing various injection moulding parameters on the wear behaviours of ultra-high molecular weight polyethylene ...(UHMWPE) with diverse performance characteristics. The injection moulding parameters are melting temperature, injection velocity and compaction time. The experimental data were used to calculate wear parameters, such as coefficient of friction, wear rate and hardness. Thirty runs were carried out using the response surface design to determine the optimal factor level condition. The graph and the response table in each level of the parameters are generated with help of grey relational grade. In addition to that, bovine serum is taken, which acts as a lubricant, and the sample hardness is tested. The results showed that there is an impact on the wear behaviour due to the contact load and melt temperature of UHMWPE. According to the grey relational grade, level 2 of injection moulding parameters has a greater effect than levels 1 and 3. With the help of a scanning electron microscope, the worn-out morphologies of samples were studied. Plastic deformation, ploughing, scratching, ironing and fatigue wear are the major wear processes of our study.
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