scholarly journals A Dimensionless Characteristic Number for Process Selection and Mold Design in Composites Manufacturing: Part I—Theory

2020 ◽  
Vol 4 (1) ◽  
pp. 11
Author(s):  
Claudio Di Fratta ◽  
Yixun Sun ◽  
Philippe Causse ◽  
François Trochu

The present article introduces a dimensionless number devised to assist composite engineers in the fabrication of continuous fiber composites by Liquid Composite Molding (LCM), i.e., by injecting a liquid polymer resin through a fibrous reinforcement contained in a closed mold. This dimensionless number is calculated by integrating the ratio of the injection pressure to the liquid viscosity over the cavity filling time. It is hereby called the “injectability number” and provides an evaluation of the difficulty to inject a liquid into a porous material for a given part geometry, permeability distribution, and position of the inlet gate. The theoretical aspects behind this new concept are analyzed in Part I of the article, which demonstrates the invariance of the injectability number with respect to process parameters like constant and varying injection pressure or flow rate. Part I also details how process engineers can use the injectability number to address challenges in composite fabrication, such as process selection, mold design, and parameter optimization. Thanks to the injectability number, the optimal position of the inlet gate can be assessed and injection parameters scaled to speed up mold design. Part II of the article completes the demonstration of the novel concept by applying it to a series of LCM process examples of increasing complexity.

2020 ◽  
Vol 4 (1) ◽  
pp. 10
Author(s):  
Claudio Di Fratta ◽  
Yixun Sun ◽  
Philippe Causse ◽  
François Trochu

The dimensionless “injectability number” was devised to assist composite engineers in the fabrication of continuous fiber composites by Liquid Composite Molding (LCM), i.e., by injecting a liquid polymer resin through a fibrous reinforcement contained in a mold cavity. Part I of this article introduced the injectability number as the integral of the ratio of the injection pressure to the resin viscosity over the cavity filling time and analyzed the theoretical aspects behind this new concept. For a given mold configuration and reinforcement material characteristics, the invariance of the injectability number with regard to process parameters was demonstrated, and an initial verification in unidirectional injection cases was conducted. Part II completes the analysis by evaluating the injectability number in more complex application cases, confirming its invariance properties. The investigation, which was carried out using numerical simulations of different LCM processes and injection strategies, examined the fabrication of various composite parts: a rectangular laminate, a hood for automotive applications, a reservoir box and a fuselage section for the aerospace industry. The results indicate that more efficient injection strategies lead to lower values of the injectability number, thus enabling the use of this dimensionless number as a tool to assess the difficulty to manufacture a given part by LCM as well as to guide process selection and compare different mold configurations.


2018 ◽  
Vol 52 (24) ◽  
pp. 3289-3297 ◽  
Author(s):  
Benoît Cosson

Tracking the variability of natural fiber-based fabrics properties, such as local areal weight, fiber volume fraction, and therefore permeability, is crucial to optimize the parts processing of the bio-composites. This paper aims at developing a cost-effective and efficient optical method in order to predict the permeability of flax fabrics used in liquid composite molding processes. This method using an LCD monitor as light source and a reflex camera as a measurement device is based on light transmission measurement through fabric thickness. The raw data given by the camera are gray scale maps, transformed into areal weight maps. FEM software based on levelset method is finally used to highlight the influence of the local variability of the fiber volume fraction, and of the related fabrics porosity and permeability on the mold filling time. The proposed method can be directly implemented on the manufacturing line of the composites. It can be used to optimize, part-to-part, the resin consumption by predicting the resin flow through perform. Interestingly, this novel optical method is auto-calibrated and does not depend on picture resolution.


2014 ◽  
Vol 1061-1062 ◽  
pp. 465-470 ◽  
Author(s):  
Bin Xu ◽  
Zhi Yuan Rui

The gating system of an injection mold for car bumper was studied. A design optimization scheme is proposed to optimize both the number and locations of the gates by analyzing the filling process, in order to reduce the part war page and weld line, numerical simulation of injection mold filling process is combined with the design optimization method to find the optimum number of gates and their locations to achieve balanced f low and less weld lines while satisfying the limit of injection pressure. Moldflow software was applied to make analysis and comparison of various gating system in terms of their filling time, injection pressure and clamp force, weld line and distribution of air traps, and an optimized gating system was obtained. The result shows that this method can effectively reduce costs, shorten development cycle and improve the efficiency of molding design.


2012 ◽  
Vol 59 (2) ◽  
Author(s):  
Mohd Fazuri Abdullah ◽  
Abu Bakar Sulong ◽  
Norhamidi Muhamad ◽  
Muhamad Afkar Husin

In the competitive world in the global market, manufacturing industry is striving to produce products at high quality, shorter time and low cost. This can be achieved through proper design activities, with assist of finite element analysis (FEA) and computer aided design (CAD). The objective of this project is to study the effect of the molding parameters on the physical characteristics of surgery tool via MIM based on design of experiment (Taguchi method). This numerical results show the behavior of feedstock entering the mould during injection process and the possibility defects that might occur. The quality of the injected product depends on the selection of the feedstock as well as the parameters for injection molding such as injection temperature (A), mold temperature (B), flow rate (C) and injection pressure (D). From the analysis of Taguchi, the optimal levels of process parameters for the shortest filling time is [A3(200ºC), B1(80ºC), C3(20 cm3/s), D3(260 MPa)]. Set of optimal parameters for the smallest shrinkage percentage difference is [A1(180ºC), B3(100ºC), C3(20 cm3/s), D2(255 MPa)]. The most influence injection molding parameters are injection temperature and injection pressure. Follow by the flow rate.


2013 ◽  
Vol 834-836 ◽  
pp. 1575-1579
Author(s):  
Bo He ◽  
Dong Hong Wang ◽  
Fei Li ◽  
Bao De Sun

As investment castings grow in size and complexity, control of wax pattern dimensions becomes increasingly important and difficult. Conventionally, mold design and dimensions are re-worked by trial-and-error procedures until casting dimensions are produced within acceptable dimensional tolerances, increasing the cost of the castings.Nowadays, numerical simulation is an efficient tool for mold design. However, one of the critical difficulties in using computer models for the simulation of wax injection process is the lack of material properties of the wax. Material property measurements were conducted in this study that can be used as input in Moldflow. Then, 3D numerical simulation could be applied in analysis with mold design of thin-walled wax pattern, with high dependability. Simulation results of filling time and the location of the air traps were analyzed. Consequently, best gate location and reasonable gate system were determined. The paper highlighted the effectiveness of simulation in filling optimization and deformation of wax pattern.


Author(s):  
Catalin Fetecau ◽  
Ion Postolache ◽  
Felicia Stan

The research presented in this paper involves numerical and experimental efforts to investigate the relative thin-wall injection molding process in order to obtain high dimensional quality complex parts. To better understand the effects of various processing parameters (the filling time, injection pressure, the melting temperature, the mold temperature) on the injection molding of a thin-wall complex part, the molding experiments are regenerated into the computer model using the Moldflow Plastics Insight (MPI) 6.1 software. The computer visualization of the filling phase allows accurate prediction of the location of the flow front, welding lines and air traps. Furthermore, in order to optimize the injection molding process, the effects of the geometry of the runner system on the filling and packing phases are also investigated. It is shown that computational modeling could be used to help the process and mold designer to produce accurate parts.


2019 ◽  
Vol 391 ◽  
pp. 30-35
Author(s):  
Iran Rodrigues de Oliveira ◽  
José Vieira da Silva ◽  
E.M. Ascendino Pereira ◽  
Sandro Campos Amico ◽  
A.G. Barbosa de Lima ◽  
...  

Resin transfer molding (RTM) is one technique that has been used to produce polymer composites, which consists in injecting a thermoset pre-catalysed resin into a closed mold containing a dry fiber preform. In this sense, this study aims to investigate the effect of the calcium carbonate content (CaCO3) in the polyester resin during the RTM process. Several experiments were conducted using glass fiber mat molded in a RTM system with cavity dimensions 320 x 150 x 3.6 mm, at room temperature, and different injection pressure (0.75 bar) and CaCO3content (0, 10, 20, 30 and 40%). Results of the physical parameters such as viscosity, permeability, and mobility, and flow front position of the resin into the mold along the RTM process are presented and analyzed. From the results was concluded that the higher the injection pressure and lower CaCO3content into the resin, the lower filling time.


Polymers ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 20 ◽  
Author(s):  
Felice Rubino ◽  
Pierpaolo Carlone

In liquid composite molding processes, such as resin transfer molding (RTM) and vacuum assisted resin transfer molding (VARTM), the resin is drawn through fiber preforms in a closed mold by an induced pressure gradient. Unlike the RTM, where a rigid mold is employed, in VARTM, a flexible bag is commonly used as the upper-half mold. In this case, fabric deformation can take place during the impregnation process as the resin pressure inside the preform changes, resulting in continuous variations of reinforcement thickness, porosity, and permeability. The proper approach to simulate the resin flow, therefore, requires coupling deformation and pressure field making the process modeling more complex and computationally demanding. The present work proposes an efficient methodology to add the effects of the preform compaction on the resin flow when a deformable porous media is considered. The developed methodology was also applied in the case of Seeman’s Composite Resin Infusion Molding Process (SCRIMP). Numerical outcomes highlighted that preform compaction significantly affects the resin flow and the filling time. In particular, the more compliant the preform, the more time is required to complete the impregnation. On the other hand, in the case of SCRIMP, the results pointed out that the resin flow is mainly ruled by the high permeability network.


Author(s):  
Chuanyang Wang ◽  
Shuai Hu ◽  
Qiubo Qian ◽  
Xuanxuan Shen

The 3D models of gating system, ejection mechanisms and cooling system of the swtich shell for injection mold are designed by using Pro/ENGINEER software. MOLDFLOW is utilized for CAE analysis. Three schemes are obtained by changing the gate location during the injection molding process. After comparing the volume shrinkage during injection, shrink marks index, filling time and the injection pressure, the best scheme is obtained. According to the optimal scheme, the injection mold is designed. The results showed that simulation analysis method can not only improve the successful probability of mold trial, but also shorten the production development cycle of developing product.


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