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Available online at www.sciencedirect.com ScienceDirect Procedia Engineering 81 (2014 ) 670 675 11th International Conference on Technology of Plasticity, ICTP 2014, 19-24 October 2014, Nagoya Congress Center, Nagoya, Japan Influence of processing parameters on molding process in microcellular injection molding Wei Guo a,b, Huajie Mao a, *, Bei Li a, Xiangyu Guo a,b a Hubei Key Laboratory of Advanced Technology for Automotive Components, Luoshi Road 122,Hongshan District, Wuhan,430070, China b Wuhan University of Technology, Luoshi Road 122, Hongshan District,Wuhan,430070, China Abstract In order to reduce weight and improve the dimensional accuracy of plastic products, microcellular injection molding technology is applied more and more in automotive. There are several defects are paid special attention by vehicle manufacturers, such as warpage and cell radius. This research investigated the effects of processing parameters in microcellular injection molding. The study investigated the influence of two kinds of gas foamers (CO 2 and N 2 ) on microcellular injection molding process, and the following processing parameters such as temperature, time, pressure and gas controlling were considered to research. Design of experiments was employed to perform the experiments. According to experimental analysis, not only the significant processing parameters to warpage were found out, but also the interactions between each factor were investigated. The results of this study could provide microcellular injection molding process design with theoretical basis and practical guidance. 2014 2014 Published The Authors. by Elsevier Published Ltd. by This Elsevier is an Ltd. open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). Selection and peer-review under responsibility of Nagoya University and Toyohashi University of Technology. Selection and peer-review under responsibility of the Department of Materials Science and Engineering, Nagoya University Keywords: Microcellular injection molding; Factorial analysis; Warpage; Processing parameters 1. Introduction Polymer raw material composes about 70% of the total cost of a plastic product, there are many scholars have done research about how to reduce the weight of plastic products, especially in automotive. The automotive plastic * Corresponding author. Tel.: +86-27-87168391; fax: +86-27-87168391. E-mail address: whutgw@whut.edu.cn 1877-7058 2014 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). Selection and peer-review under responsibility of the Department of Materials Science and Engineering, Nagoya University doi:10.1016/j.proeng.2014.10.058

Wei Guo et al. / Procedia Engineering 81 ( 2014 ) 670 675 671 products demand both lightweight and high dimensional accuracy. The microcellular injection molding is employed to reduce the products weight, because the presence of foam cells in the polymer decreases the density of the material, which ensures using less row material. Furthermore, the morphological structure of foam cells can be arranged via controlling the porosity ratio in polymer, so different microcellular foam polymer with varying properties can be generated by using microcellular injection molding, which are proper to be used in different industrial area. In an attempt to understand the effect of processing parameters, Hong-Bin Wu applied the MuCell technology to produce an open porous polyurethane structure to identify the key processing parameters and try to quantify the main processing parameters which govern the open pore structure and morphology. They found that the gas content and weight reduction makes a more profound effect on the pore morphology [1]. Jaime Francisco analyzed the effects of several typical injection molding parameters on the foam morphology, apparent density and thermomechanical properties of PETG, trying to provide knowledge on microcellular injection molding parameters to control PETG and establish a correlation between the cellular structure and thermal properties and Bo Xie investigated the influence of processing parameters on the foam morphology and its mechanical properties on the parts [3-5]. In 1999, using a pressure vessel, Handa investigated the influence of variables (foaming temperature, foaming time, saturating pressure) on the resulting microcellular foam properties on PETG film samples, also in a batch process [6]. In 2010, Kanehashi analyzed the solubility of gases (CO2, O2 and N2) in crystalline polymers (PET among them), which tends to decrease with increasing crystallinity [7]. That same year, Sorrentino investigated the foam ability of two high molecular weight PETs, performing sorption tests to determine the solubility and diffusivity of CO2 and N2 in these two polymers [8]. Salih Hakan designed a series of experiments to study influence of injection pressure and melting temperature on the average cell dimension, cell number, skin layer thickness, foam density and mechanical properties of investigated foam materials were evaluated. It can be learned from the results that cell density is increased by the increment of injection pressure [9]. Chien, using a chemical foam agent, produced PP foams. They investigated the effects of injection speed, the temperature of molten material and molding, and feedback pressure onto the part thickness, and mechanical properties [10]. In the present study, a plastic product made of PP+EPDM+20%Talc was chosen as research object. The CAE software MoldFlow was employed to investigate the influence of the gas foam type and processing parameters on microcellular injection molding process. DOE was used to find out the significant processing parameters to warpage and sink mark, furthermore, the interactions between each processing parameters were also investigated. 2. Experimental setup The aim of this section is to illuminate the geometry model and finite element model of the part and mold, and to explain the thermoplastic material of the part. Fig. 1. 3D model and dimensioning of standard tensile. Fig. 2. FE model of product and mold. 2.1. Geometry model and thermoplastic material In order to investigate the influence of processing parameters on product defect and product performance, a 3D geometry model is necessary. Hence, the standard tensile sample was selected as a research object, which was established in UG according to ISO 527-2, the dumbbell tensile test specimen was moulded as the following size: Gauge length (L 0 =50.0), Length of narrow parallel-sided portion (L 1 =80.0), Distance between broad parallel-sided portions (L 2 =110), Overall length (L 3 =150), Width of narrow portion (b 1 =10.0), Width at ends (b 2 =20.0),

672 Wei Guo et al. / Procedia Engineering 81 ( 2014 ) 670 675 Preferred thickness (h=4.0), which is shown in Fig. 1. A proper mold design is a necessity to assure accomplishment of the product injection. Hence, the runner system and cooling system were established in MoldFlow software according the standard mold design guidelines, which is shown in Fig. 2. The thermoplastic material for conducting the finite element analysis is selected from the MoldFlow software. The material structure is crystalline. Its properties were given in Table 1. 2.2. FE model of the part and mold The 3D geometry model was imported into the CAE software MoldFlow through format conversion. A midplane finite element model was created by meshing the 3D model with 369 linear triangular elements. The average aspect ratio of the mesh was 1.51, and the maximum of aspect ratio was 3.0. The mesh was thoroughly checked to eliminate mesh-related errors, which is shown in Fig. 2. Meanwhile, the FE model of runner system and cooling system were also created by using meshing tools in MoldFlow, which is shown in Fig. 2. Table 1. Properties of material. Material Description Mechanical properties Solid density (g/cm 3 ) 0.90211 Elastic modulus (MPa) 918.603 Melt density (g/cm 3 ) 0.77072 Shear modulus (MPa) 329.589 Ejection temperature ( o C) 115 Poisson s ratio 0.3936 Material characteristics Filler PP+EPDM 20% Talc 3. Experimental method The purpose of this study was to investigate the influence of processing parameters on microcellular injection molding. In the first section, fractional factorial design method was employed to conduction to identify the most influential variables to warpage. In the second section, the four most influential factors were selected as research object, which were identified on the basis of fractional factorial design. 3.1. Experiments of foamer analysis The altering of foaming agent will affect not only the microcellular structure of products but also injection defect, such as warpage, volume shrinkage and sink mark depth so on. The molding quality is directly related to the dimension precision and mechanical properties of products, so there are close relationship between the foaming agent and product quality. Nitrogen and carbon dioxide are the two kinds of gas foaming agent which are commonly used in microcellular foam injection molding. In this section, CO 2 and N 2 were selected as study object. While the foaming agent was being altered, the other processing parameters were kept in a fixed level. The influence of foaming agent on microcellular injection molding and injection defects was investigated by conducting CAE experiments. 3.2. Factorial analysis There are three kinds of factors affect the value of warpage in microcellular injection molding, such as material, product design, and manufacturing processing. In this study, the injection defects were reduced by controlling the processing parameters. However, there are many parameters in injection processing, it is difficult to find out the influence of the parameters on warpage at the same time. Fractional factorial design can be used to investigate the effects of two or more factors, it is more efficient than one-factor-at-a-time experiments. In the present study, the following parameters are selected as subject investigated: flow rate, V/P switch-over, mold temperature, melt temperature, coolant temperature, coolant, volume filled at start of foaming, initial bubble radius, number of cells per volume, initial gas concentration. In this section, L 32 array are employed to investigate the

Wei Guo et al. / Procedia Engineering 81 ( 2014 ) 670 675 673 influence of the selected parameters on warpage. The processing parameters and their levels selected are indicated in Table 2. Table 2. The processing parameters and their levels. No Processing parameters Levels Levels No Processing parameters Low (-1) High (1) Low (-1) High (1) 1 Mold temperature ( o C) 40 80 6 V/P switch over 95% 99% 2 Melt temperature ( o C) 200 240 7 Initial foaming volume 90% 95% 3 Coolant temperature ( o C) 25 50 8 Initial bubble radius (mm) 0.001 0.005 4 C 8000 12000 9 Cell number (1/m 3 ) 2e+011 5e+011 5 Flow rate (cm 3 /s) 500 800 10 Initial gas concentration 0.5% 1% 4. Results and analysis 4.1. Analysis of foamer selected In this section, the CAE experiments with different foamer were carried out in MoldFlow. The main results were recorded as shown in Fig. 3. Fig. 3(a) shows the different warpage results of key nodes on the FE model, which were collected from the CAE analysis by using different foaming agent. Nodes 67-73 are on the continuous area in the middle of the tensile spline, node 70 is in the central of the FE model. It is observed that, the warpage changed trends under different foaming agent are coincident, which can be summarized as follow: warpage of central product is minimum, and warpage increases gradually from the center to both ends of the tensile spline. It also can be found that warpage of each sample region under N 2 are less than under CO 2. The reason related to the solubility of a gas in the melt, the solubility of CO 2 is higher than N 2 under the same temperature and pressure condition. The viscosity of the melt including N 2 is smaller than the melt including CO 2, so the melt including N 2 has better filling property, which will reduce the residual stress in injection molding. The sample can be divided into three parts along the thickness direction, which are surface layer, interlayer and core layer. The elasticity modulus and bubble radius of different layers under various foaming agents are shown in Fig. 3(b/c). It is observed that, there are highest elastic modulus and smallest bubble radius in surface layer, and there are lowest elastic modulus and largest bubble radius in core layer. Elastic modulus changing trend with the thickness direction is opposite to bubble radius, the reason is that the effective stress area under tensile loading is diminishing with the increasing of bubble radius. It also can be found that, the bubble radius of interlayer and core layer under N 2 are smaller than under CO 2, and the radius of surface layer under N 2 is larger than under CO 2. Fig. 3. Influence of foaming agent on microcellular injection: (a) warpage results with different foamer; (b) elastic modulus of critical area with different foamer; (c) bubble radius of critical area with different foamer. 4.2. Analysis of FFD experiments In this chapter, a total number of 32 trails were carried out and the maximum values of warpage were collected from MoldFlow. The values tabulated in Table 4 were imported into the software Minitab to actualize factorial

674 Wei Guo et al. / Procedia Engineering 81 ( 2014 ) 670 675 analysis. The importance of the ten influence parameters to warpage is charted in Fig. 4. The meaning of the distance between the points and the blue oblique line is about the influence degree of the factor. It indicated that the influence of initial foaming volume, interaction between coolant temperature, mold temperature and interaction between mold temperature and coolant temperature is significant. Significant influence of the factor interaction is shown in Fig. 5. In light of Fig. 5, the following observations can be obtained: (1) it will increase warpage that enhances coolant temperature and mold temperature. In other words, low mold temperature and coolant temperature have a positive influence on reducing warpage. (2) it will reduce warpage with enhanc low mold temperature and large initial bubble radius have a positive influence on reducing warpage. Table 4. FFD array and warpage results. No Mold temp Melt temp Coolant temp Coolant number Flow rate V/P switchover Initial foaming volume Initial bubble radius Cell number Initial gas concen Warpage (mm) 1-1 1 1-1 -1 1 1-1 -1 1 1.0950 2-1 1 1-1 1 1-1 1 1-1 0.9367 3 1 1-1 1-1 -1 1-1 1 1 1.0930 4 1-1 -1 1-1 1-1 1 1-1 1.3270 5-1 -1 1 1 1 1 1 1-1 -1 1.1850 6-1 1 1 1-1 -1 1 1 1-1 0.7697 7 1-1 1 1 1-1 -1-1 1-1 0.8401 8 1-1 1-1 1 1-1 1-1 1 0.8615 9-1 -1 1-1 1-1 1-1 1 1 1.1850 10-1 -1-1 -1 1 1-1 -1-1 -1 0.4046 11 1 1 1-1 -1-1 -1 1 1 1 0.7893 12-1 -1-1 -1-1 1 1 1 1 1 0.7971 13 1 1 1 1 1 1 1 1 1 1 0.8691 14 1 1-1 -1 1 1-1 -1 1 1 0.7118 15 1-1 -1-1 1-1 1 1 1-1 1.1850 16 1 1-1 -1-1 1 1 1-1 -1 1.0950 17-1 -1-1 1 1-1 -1 1 1 1 0.7807 18-1 1 1 1 1-1 -1-1 -1 1 0.8152 19-1 -1 1-1 -1-1 -1 1-1 -1 0.5678 20-1 1-1 1 1 1 1-1 1-1 1.0910 21-1 -1-1 1-1 -1 1-1 -1-1 1.1860 22 1 1-1 1 1-1 -1 1-1 -1 1.3100 23-1 -1 1 1-1 1-1 -1 1 1 0.8292 24 1-1 1-1 -1 1 1-1 1-1 1.1860 25 1 1 1 1-1 1-1 -1-1 -1 0.7522 26-1 1-1 -1-1 -1-1 -1 1-1 0.6626 27-1 1-1 1-1 1-1 1-1 1 0.6364 28 1-1 -1 1 1 1 1-1 -1 1 1.1840 29 1 1 1-1 1-1 1-1 -1-1 1.0940 30-1 1-1 -1 1-1 1 1-1 1 0.7075 31 1-1 -1-1 -1-1 -1-1 -1 1 0.7254 32 1-1 1 1-1 -1 1 1-1 1 1.1920 Fig. 4. Influence degree of factors to warpage: (a) half normal plot of the effects; (b) pareto chart of the effects.

Wei Guo et al. / Procedia Engineering 81 ( 2014 ) 670 675 675 Fig. 5. Surface plots of the interaction: (a) interaction between mold temperature and coolant temperature; (b) interaction between coolant. 5. Conclusion In this study, the standard tensile sample was selected as a research object. The 3D model and FE model of the sample and mold were established in Unigraphics and MoldFlow in order to investigate the influence of foaming agent and processing parameters on microcellular injection molding process. The variations of warpage, bubble radius and mechanical property of the sample under different foamers were revealed by using CAE analysis. Under the analysis of FFD, it was found that the influence of initial foaming volume and mold temperature was significant, and other significa and melt temperature in order. Acknowledgements 2013AA040201) and th the Central Universities (WUT: 2014-IV-041). References [1] Hong-Bin, Wu, Håvard, J., Haugen, Erich, Wintermantel, 2012. Supercritical in injection molding can produce open porous polyurethane scaffolds -a parameter study. Journal of Cellular Plastics 48, 141 159. [2] Jaime Francisco, Gómez-Gómez, David Arencón, Miguel Ángel Sánchez-Soto and Antonio B. Martínez, 2012. Influence of the injection moulding parameters on the microstructure and thermal properties of microcellular polyethylene terephthalate glycol foams. Journal of Cellular Plastics 0(00), 1 17. [3] ameters. Journal of Cell Plast 43, 313 330. [4] Processing 5, 399 405. [5] ecycled Polypropylene) Composites[J]. Journal of Vinyl & Additive Technology 10.1002, 105 112. [6] Handa YP, Wong B, Zhang Z, 1999. Some thermodynamic and kinetic properties of the system PETG-CO2, and morphological characteristics of the CO2-blown PETG foams. Polymer Engineering and Science 39, 55 61. [7] Kanehashi S, Kusakabe A, Sato S, 2010. Analysis of permeability; solubility and diffusivity of carbon dioxide; oxygen; and nitrogen in crystalline and liquid crystalline polymers. Journal of Membrane Science 365, 40 51. [8] Sorrentino L, Di Maio E and Iannace S, 2010. Poly(ethylene terephthalate) foams: correlation between the polymer properties and the foaming process. Journal of Applied Polymer Science 116, 27 35. [9] Salih Hakan Yetkin, Huseyin Unal, Abdullah Mimaroglu, Fehim Findik, 2013. Influence of Process Parameters on the Mechanical and Foaming Properties of PP Polymer and PP/TALC/EPDM Composites. Polymer-Plastics Technology and Engineering 52, 433 439. [10] J.S, 2004. Study on the molding characteristics and mechanical properties of injection-molded foaming polypropylene parts. J. Polymer Composites 23(4), 429 444.