Injection Molding Process Parameters Research Articles

Compensating additional optical power in the central zone of a multifocal contact lens forminimization of the shrinkage error of the shell mold in the injection molding process.

This study aims to develop a compensating method to minimize the shrinkage error of the shell mold (SM) in the injection molding (IM) process to obtain uniform optical power in the central optical zone of soft axial symmetric multifocal contact lenses (CL). The Z-shrinkage error along the Z axis or axial axis of the anterior SM corresponding to the anterior surface of a dry contact lens in the IM process can be minimized by optimizing IM process parameters and then by compensating for additional (Add) powers in the central zone of the original lens design. First, the shrinkage error is minimized by optimizing three levels of four IM parameters, including mold temperature, injection velocity, packing pressure, and cooling time in 18 IM simulations based on an orthogonal array L18 (21×34). Then, based on the Z-shrinkage error from IM simulation, three new contact lens designs are obtained by increasing the Add power in the central zone of the original multifocal CL design to compensate for the optical power errors. Results obtained from IM process simulations and the optical simulations show that the new CL design with 0.1 D increasing in Add power has the closest shrinkage profile to the original anterior SM profile with percentage of reduction in absolute Z-shrinkage error of 55% and more uniform power in the central zone than in the other two cases. Moreover, actual experiments of IM of SM for casting soft multifocal CLs have been performed. The final product of wet CLs has been completed for the original design and the new design. Results of the optical performance have verified the improvement of the compensated design of CLs. The feasibility of this compensating method has been proven based on the measurement results of the produced soft multifocal CLs of the new design. Results of this study can be further applied to predict or compensate for the total optical power errors of the soft multifocal CLs.

Simulation Analysis to Optimize the Parameters of Injection Molding Process to Improve the Residual Stress of Sprinkler Body

Simulation Analysis to Optimize the Parameters of Injection Molding Process to Improve the Residual Stress of Sprinkler Body

Optimization of Recycled Glass Fibre-Reinforced Plastics Gear via Integration of the Taguchi Method and Grey Relational Analysis

The increase in demand for industrial gears has resulted in the increase in usage of plastic-matrix composites particularly glass fibre-reinforced plastics as the gear materials. The usage of these synthetic fibers is to enhance the mechanical strength and the thermal resistance of the plastic gears. Nevertheless, the production of large quantities of these synthetic fibre-reinforced composites poses a serious threat to the ecosystem. Comprehending to this fact, the present work aimed at investigating the effects of incorporating recycled glass fibre-reinforced plastics in various compositions particularly on dimensional stability and mechanical properties of gear produced with diverse injection moulding processing parameters setting. The integration of Grey relational analysis (GRA) and Taguchi method was adopted to evaluate the influence of recycled glass fibre-reinforced plastics and variation in processing parameters on gear quality. From the experimental results, the blending ratio was found as the most influential parameter of 56.0% contribution in both improving tensile properties as well as in minimizing shrinkage, followed by mould temperature of 24.1% contribution and cooling time of 10.6% contribution. The results obtained from the aforementioned work are expected to contribute to accessing the feasibility of using recycled glass fibre-reinforced plastics especially for gear application.

Investigation of injection molding parameters on the uniformity of porous array of polymer microfluidic chip

The uniformity of the porous array seriously affects the performance of the injection-molded parts. In this study, a uniform hole array chip constituted by 384 holes whose radiuses are 1.30 mm is fabricated by precision injection molding technology. To capture the relevance between the uniform dimension of the porous array and the injection molding process parameters, single factor experiment was adopted. Besides, the condensed state of the hole array was studied to give a further explanation of the inner relationship between the hole array and the most sensitive injection process. As for the measurement, the diameter of the hole which next to the gate and away from the gate was investigated by means of universal tool-measuring microscope, and the standard deviation of the hole diameter was chosen to estimate the uniformity of the hole array. Furthermore, the crystal state and interface state were characterized by polarized light microscopy (PLM), used to explain why the difference of those holes appeared. The results reveal that the impact of process parameters on the uniformity of the hole array was ranked as follows: melt temperature, cooling time, mold temperature, injection pressure, injection speed and packing pressure. Besides, the analysis of the condensed state on different melt temperature indicates that the larger grain size is less favorable to the uniform molding, as the melt temperature increases, the difference of cortical thickness between the dynamic template and fixed template sides decreases, product uniformity is improved.

Effect of Process Parameters on Flow Length and Flash Formation in Injection Moulding of High Aspect Ratio Polymeric Micro Features.

This paper reports an investigation of the effects of process parameters on the quality characteristics of polymeric parts produced by micro injection moulding (μIM) with two different materials. Four injection moulding process parameters (injection velocity, holding pressure, melt temperature and mould temperature) were investigated using Polypropylene (PP) and Acrylonitrile Butadiene Styrene (ABS). Three key characteristics of the mouldings were evaluated with respect to process settings and the material employed: part mass, flow length and flash formation. The experimentation employs a test part with four micro fingers with different aspect ratios (from 21 up to 150) and was carried out according to the Design of Experiments (DOE) statistical technique. The results show that holding pressure and injection velocity are the most influential parameters on part mass with a direct effect for both materials. Both parameters have a similar effect on flow length for both PP and ABS at all aspect ratios and have higher effects as the feature thickness decreased below 300 μm. The study shows that for the investigated materials the injection speed and packing pressure were the most influential parameters for increasing the amount of flash formation, with relative effects consistent for both materials. Higher melt and mould temperatures settings were less influential parameters for increasing the flash amount when moulding with both materials. Of the two investigated materials, PP was the one exhibiting more flash formation as compared with ABS, when corresponding injection moulding parameters settings for both materials were considered.

Metal Injection Molding Process Parameters as A Function of Filling Performance of 3D Printed Polymer Mold

Metal injection molding (MIM) is a swift manufacturing process, which can produce complex and intricate parts with good repeatability and accuracy. However, to quickly address low-volume demands of customized MIM parts, manufacturing of mold could be a potential challenge. Typically, machined metal molds are used for MIM, but they are expensive and need more lead time. The machined metal mold becomes useless once the design is changed or requirement of MIM parts is met. Therefore, for MIM production of a low volume of highly customized parts, machined metal mold could be substituted by 3D printed polymer molds. However, knowledge of filling behavior of MIM feedstock in polymer mold is a grey area, which demands study to investigate the effects of injection parameters on mold filling. The present study investigates the effects of machine injection parameters on feedstock filling behavior in 3D printed polymer molds. An attempt has been made to determine the trend of feedstock filling in the polymer mold as a function of injection parameters. Further, the design of experiment (DOE) has been used to estimate the weight of injection parameters.

Multi Response optimization of injection moulding Process parameters to reduce cycle time and warpage

The research paper is approach for multi response optimization of injection moulding process parameters. In this Taguchi and desirability function hybridization approach is used. The experiments are plotted using L27 orthogonal array, which is generated with the help of MINITAB-14 software. The process parameters injection pressure, melt temperature, packing time, packing pressure are optimized by multiple response consideration using cycle time and warpage. With the help of the composite desirability value after the desirability function analysis optimal values of process parameters is obtained. The analysis shows optimized process parameters combination of injection pressure, melt temperature, packing time and packing pressure. Confirmation test is also carried to minimization of error of experiments. Experimental result shows that by this injection moulding machine performance can be improved. Injection moulded product has been made by this approach by using virgin Poly propylene. It is thin walled products for the measurement of warpage and cycle time.

Application of Taguchi Method-Moldflow-Particle Swarm Optimization for Plastic Injection Process Parameters Optimization

Plastic injection process is one of techniques used to manufacture plastic products. The technique is widely used due to its higher and faster production capacity and low cost. However, production process problems are often found, one of which is inappropriate process parameters settings, which may cause product defects. This paper presents a method using combination of Taguchi method, Moldflow simulation and PSO to optimize plastic injection molding process parameters. Moldflow simulations were run to obtain volumetric shrinkage values resulting from each combination of parameters setting selected by means of OA. In adopting S/N ratio technique of Taguchi method, study adhered to principle of the smaller better. The ANOVA method was also used to analyze effect of each process parameter on volumetric shrinkage and a regression analysis was used to establish equation used for application of PSO method to optimize plastic injection process parameters. This method was applied for production of number plate brackets from PP AZ564 material. The study concluded that application of combined Taguchi-Moldflow-PSO method could reduce volumetric shrinkage from 6.05% to 4.24%.

A Comparative Analysis of Taguchi Methodology and Shainin System DoE in the Optimization of Injection Molding Process Parameters

Two well-known Design of Experiments (DoE) methodologies, such as Taguchi Methods (TM) and Shainin Systems (SS) are compared and analyzed in this study through their implementation in a plastic injection molding unit. Experiments were performed at a perfume bottle cap manufacturing company (made by acrylic material) using TM and SS to find out the root cause of defects and to optimize the process parameters for minimum rejection. Experiments obtained the rejection rate to be 8.57% from 40% (appx.) during trial runs, which is quiet low, representing successful implementation of these DoE methods. The comparison showed that both methodologies gave same set of variables as critical for defect reduction, but with change in their significance order. Also, Taguchi methods require more number of experiments and consume more time compared to the Shainin System. Shainin system is less complicated and is easy to implement, whereas Taguchi methods is statistically more reliable for optimization of process parameters. Finally, experimentations implied that DoE methods are strong and reliable in implementation, as organizations attempt to improve the quality through optimization.

Estimating energy consumption of injection moulding for environmental-driven mould design

Supporting environmentally-conscious design of moulds is the ultimate objective of the here presented advisory tool. Relying on a careful estimation of the energy used for the injection moulding process, the designer is guided towards the development of green(er) solutions. As shown by literature and through a preliminary LCA screening analysis, most of the environmental impacts of a mould are directly connected to the energy consumed during the injection phase. This paper proposes a guideline for a reliable and sensitive energy estimation of the injection moulding process, taking into account not only the part and the material to be moulded, but also the specifications of the mould, the injection moulding machine and the injection moulding process parameters. The accurate estimation of the energy consumed may radically improve the estimation of the overall environmental impacts of the mould and of the moulded product, and provide a value-added support for eco-driven decision making since the mould design phase. This work aims at contributing to the development of new methodologies to help injection moulding industry to develop more sustainable parts, moulds and processes.

Numerical Optimization of Shrinkage and Warpage on the Injection Molding Process Parameters of Electrical Connector

Integrated with orthogonal design method and numerical simulation, injection molding process of the Y-type electrical connectors was conducted to study the influence of process parameters on volume shrinkage rate and maximum warpage, which are regarded as product quality indices. The multi-indices valuation model for the main influencing factors of the process is developed. The influencing sensitivity to the multi-objective of the processing parameters, such as melt temperature, mold temperature, injection time and holding pressure, is determined by range analysis. Through analyzing the diagrams of influential factors, the optimized process parameter diagram is obtained and verified by simulation. The optimum parameters minimizing the warpage defect and shrinkage are: melt temperature (528K), mold temperature (338K), filling time (0.6s), holding pressure (100%) and holding time (10s). The results show that it is effective to balance the impact of process parameters on the shrinkage and warpage. The work can provide optimal design and process reference for the quality control and assembly precision.

Effects of machined cavity texture on ejection force in micro injection molding

The friction force developed in the demolding phase of the micro injection molding process is mainly determined by mold surface finish, which affects the tribological phenomena occurring at the polymer–tool interface. In this work, the effects on the ejection force of two cavity surfaces machined with different technologies (viz. micro milling and micro electro discharge machining), but with similar value of Ra, were investigated. The relations between different surface topography parameters and the ejection force were then analyzed, in order to identify the parameters that most appropriately describe the friction at the polymer–tool interface. The experimental results showed the strong interactions between the mold surface texture and the micro injection molding process parameters that promote the replication, such as mold temperature and holding pressure. The different machining technologies generated two mold textures that have a similar value of Ra, but their influence on friction can be properly described only using several other surface topography parameters.

Influence of the Processing Parameters on the Fiber-Matrix-Interphase in Short Glass Fiber-Reinforced Thermoplastics.

The interphase in short fiber thermoplastic composites is defined as a three-dimensional, several hundred nanometers-wide boundary region at the interface of fibers and the polymer matrix, exhibiting altered mechanical properties. This region is of key importance in the context of fiber-matrix adhesion and the associated mechanical strength of the composite material. An interphase formation is caused by morphological, as well as thermomechanical processes during cooling of the plastic melt close to the glass fibers. In this study, significant injection molding processing parameters are varied in order to investigate the influence on the formation of an interphase and the resulting mechanical properties of the composite. The geometry of the interphase is determined using nano-tribological techniques. In addition, the influence of the glass fiber sizing on the geometry of the interphase is examined. Tensile tests are used in order to determine the resulting mechanical properties of the produced short fiber composites. It is shown that the interphase width depends on the processing conditions and can be linked to the mechanical properties of the short fiber composite.

Multiobjective Optimization of Injection Molding Process Parameters for the Precision Manufacturing of Plastic Optical Lens

Injection molding process parameters (IMPP) have a significant effect on the optical performance and surface waviness of precision plastic optical lens. This paper presents a set of procedures for the optimization of IMPP, with haze ratio (HR) reflecting the optical performance and peak-to-valley 20 (PV20) reflecting the surface waviness as the optimization objectives. First, the orthogonal experiment was carried out with the Taguchi method, and the results were analyzed by ANOVA to screen out the IMPP having a significant effect on the objectives. Then, the 34 full-factor experiment was conducted on the key IMPP, and the experimental results were used as the training and testing samples. The BPNN algorithm and the M-SVR algorithm were applied to establish the mapping relationships between the IMPP and objectives. Finally, the multiple-objective optimization was performed by applying the nondominated sorting genetic algorithm (NSGA-II), with the built M-SVR models as the fitness function of the objectives, to obtain a Pareto-optimal set, which improved the quality of plastic optical lens comprehensively. Through the experimental verification on the optimization results, the mean prediction error (MPE) of HR and PV20 is 7.16% and 9.78%, respectively, indicating that the optimization method has high accuracy.

Evaluation of Injection Molding Process Parameters for Manufacturing Polyethylene Terephthalate

Quality control is an important aspect in manufacturing process. The quality of product in injection moulding is influenced by injection moulding process parameter. In this study, the effect of injection moulding parameter on defects quantity of PET preform was investigated. Optimizing the parameter of injection moulding process is critical to enhance productivity where parameters must operate at an optimum level for an acceptable performance. Design of Experiment (DOE) by factorial design approach was used to find an optimum parameter setting and reduce the defects. In this case study, Minitab 17 software was used to analyses the data. The selected input parameters were mould hot runner temperature, water cooling chiller temperature 1 and water cooling chiller temperature 2. Meanwhile, the output for the process was defects quantity of the preform. The relationship between input and output of the process was analyzed using regression method and Analysis of Variance (ANOVA). In order to interpolate the experiment data, mathematical modeling was used which consists of different types of regression equation. Next, from the model, 95% confidence level (p-value) was considered and the significant parameter was figured out. This study involved a collaboration with a preform injection moulding company which was Nilai Legasi Plastik Sdn Bhd. The collaboration enabled the researchers to collect the data and also help the company to improve the quality of its production. The results of the study showed that the optimum parameter setting that could reduce the defect quantity of preform was MHR= 88°C, CT1= 24°C and CT2= 27°C. The comparison defect quantity analysis between current companies setting with the optimum setting showed improvement by 21% reduction of defect quantity at the optimum setting. Finally, from the optimization plot, the validation error between the prediction value and experiment was 1.72%. The result proved that quality of products can be improved by using the DOE approach.

The simulation of the warpage rule of the thin-walled part of polypropylene composite based on the coupling effect of mold deformation and injection molding process

Abstract Aiming at the problem that a thin-walled plastic part easily produces warpage, an orthogonal experimental method was used for multiparameter coupling analysis, with mold structure parameters and injection molding process parameters considered synthetically. The plastic part deformation under different experiment schemes was comparatively studied, and the key factors affecting the plastic part warpage were analyzed. Then the injection molding process was optimized. The results showed that the important order of the influence factors for the plastic part warpage was packing pressure, packing time, cooling plan, mold temperature, and melt temperature. Among them, packing pressure was the most significant factor. The optimal injection molding process schemes reducing the plastic part warpage were melt temperature (260°C), mold temperature (60°C), packing pressure (150 MPa), packing time (2 s), and cooling plan 3. In this situation, the forming plate flatness was better.

Minimization of variation in volumetric shrinkage and deflection on injection molding of Bi-aspheric lens using numerical simulation

The profile of a bi-aspheric lens is such a way that the thickness narrows down from center to periphery (convex). Injection molding of these profiles has high shrinkage in localized areas, which results in internal voids or sink marks when the part gets cool down to room temperature. This paper deals with the influence of injection molding process parameters such as mold surface temperature, melt temperature, injection time, V/P Switch over by percentage volume filled, packing pressure, and packing duration on the volumetric shrinkage and deflection. The optimal molding parameters for minimum variation in volumetric shrinkage and deflection of bi-aspheric lens have been determined with the application of computer numerical simulation integrated with optimization. The real experimental work carried out with optimal molding parameters and found to have a shallow and steep surface profile accuracy of 0.14 and 1.57 mm, 21.38-45.66 and 12.28-26.90 μm, 41.56-157.33 and 41.56-157.33 nm towards Radii of curvatures (RoC), surface roughness (Ra) and waviness of the surface profiles (profile error Pt), respectively.

The effect of injection molding process parameters on mechanical and fracture behavior of polycarbonate polymer

ABSTRACTIn this work, the mechanical and failure behavior of injection molded aviation standard optical grade polycarbonate (PC) was investigated through uniaxial tensile testing. The effect of different injection molding process parameters including injection velocity, packing pressure, cooling time, mold temperature, and melt temperature were determined to observe their effect on yield and postyield behavior of PC. Out of these examined parameters, the mold and melt temperature show significant effect on mechanical behavior of studied polymer. The yield and flow stresses in polymer increase with the increase in mold and melt temperature during injection molding. However, other process parameters i.e., packing pressure, injection velocity, and cooling time showed little effect on mechanical performance of the polymer. The molded specimens were annealed at different temperatures and residence time to evaluate its effect on mechanical behavior and fracture morphology. The yield stress increases gradually with the increase in annealing temperature and time. The annealing treatment also changed the failure mode of PC specimens from ductile to brittle. In addition to process parameters, the effect of increased loading rate was also undertaken which shows substantial effect on mechanical and failure behavior of PC. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 44474.

Multi-objective optimization of injection molding process parameters in two stages for multiple quality characteristics and energy efficiency using Taguchi method and NSGA-II

In this paper, the parameters optimization of plastic injection molding (PIM) process was obtained in systematic optimization methodologies by two stages. In the first stage, the parameters, such as melt temperature, injection velocity, packing pressure, packing time, and cooling time, were selected by simulation method in widely range. The simulation experiment was performed under Taguchi method, and the quality characteristics (product length and warpage) of PIM process were obtained by the computer aided engineering (CAE) method. Then, the Taguchi method was utilized for the simulation experiments and data analysis, followed by the S/N ratio method and ANOVA, which were used to identify the most significant process parameters for the initial optimal combinations. Therefore, the range of these parameters can be narrowed for the second stage by this analysis. The Taguchi orthogonal array table was also arranged in the second stage. And, the Taguchi method was utilized for the experiments and data analysis. The experimental data formed the basis for the RSM analysis via the multi regression models and combined with NSGS-II to determine the optimal process parameter combinations in compliance with multi-objective product quality characteristics and energy efficiency. The confirmation results show that the proposed model not only enhances the stability in the injection molding process, including the quality in product length deviation, but also reduces the product weight and energy consuming in the PIM process. It is an emerging trend that the multi-objective optimization of product length deviation and warpage, product weight, and energy efficiency should be emphasized for green manufacturing.

A study of effect of injection molding process parameters on the impact performance of plastic product fabricated by fine fillers filled LDPE

A study of effect of injection molding process parameters on the impact performance of plastic product fabricated by fine fillers filled LDPE