The 9th Asian Symposium on VisualizationHong Kong, 4-8 June, 2007

ASV0056-003

ASV0056-003-1

A Simulation and Optimization of Rubber Injection Molding Process

R. Panyawipart 1, S. Rodkwan 2 and C. Raksiri 3

1.Center of Excellence in Rubber Mould, Research and Development Institute of Industrial Production Technology and Department of Mechanical Engineering, Faculty of Engineering, Kasetsart University,

Bangkok, Thailand. E-mail: rungtham.p@ku.ac.th 2.Center of Excellence in Rubber Mould, Research and Development Institute of Industrial Production Technology and Department of Mechanical Engineering, Faculty of Engineering, Kasetsart University,

Bangkok, Thailand. E-mail: fengssr@ku.ac.th 3.Center of Excellence in Rubber Mould, Research and Development Institute of Industrial Production Technology and Department of Industrial Engineering, Faculty of Engineering, Kasetsart University,

Bangkok, Thailand. E-mail:chana_raksiri@yahoo.com

Corresponding author R. Panyawipart

Abstract This research aims to apply Computer Aided Design/Engineering (CAD/CAE) techniques for an optimized rubber injection molding condition using a case study of rubber steps used in motorcycles. The input parameters include both physical and mechanical material properties of natural rubber and operating conditions such as gating and runner positions. The simulated variables such as temperature, pressure and velocity profiles were founded and analyzed. The numerical results are correlated well with empirical data using the vertical injection molding machine. This research provides researchers the computational tool to obtain the optimized rubber injection molding.

Keyword: Computer Aided Design/ Engineering (CAD/CAE), Rubber Injection Molding, Simulation 1. Introduction Generally, rubber products can be formed into various shapes through molding, calendaring, and extrusion processes. In molding, it can be further classified into three processes: injection, compression and transfer molding [1]. Most complicated rubber molded parts such shoe soles, engine mountings are produced using injection molding process. Nevertheless, there is still lack of the overall understanding of the rubber injection process which leads to product degradation such as excessive flash, air trap and overcured section. In addition, rubber mold design and making technology is still one of the significant obstacles in rubber product industry. Consequently, this research is proposed to use a numerical tool such as Computer Aided Design/Engineering (CAD/CAE) techniques for an optimization of natural rubber injection molding process of a selected automotive rubber part. This can lead to better understanding of molding injection conditions and higher quality of rubber products.

2. Materials and Methods There are four factors to include in this research: rubber material, injection machine, rubber mold and simulation. Motorcycle rubber steps made of natural rubber (NR-40), as shown in Fig.1, were selected for a case study. The vertical rubber injection machine (Nissei, Model TH100-25VSER, as shown in Fig. 2), which has a maximum clamp force of 100 tons, and a cavity volume of 254 cm3, was used in this work. Mold component was designed as illustrated in Fig. 3. The main part consists of bushings, slide core, guide pin, cavity block, and heater. The core and cavity plates were shown in Fig. 4.

R. Panyawipart, S. Rodkwan and C. Raksiri

ASV0056-003-2 9th Asian Symposium on Visualization, Hong Kong SAR, China, 2007.

Fig. 1. a) Motorcycle rubber step. b) CAD file for Motorcycle rubber step.

Fig. 2. Vertical rubber injection machine.

Top Clampingplate

Cavity Block

Cavity Block

Heater (Top)

Heater (Bottom)

Locating Ring

Screw

Slide Core

Bottom plate

Spcer Block

Spcer Block2

Sprue Bushings

Bushing

Support Plate

Cover Slide

Fig. 3. Mold components.

(a) (b)

A Simulation and Optimization of Rubber Injection Molding Process

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Fig. 4. Core and cavity plates. 2.1 Simulation of Rubber Injection Molding The CAD data is transferred into 3D-SIGMA, a rubber injection simulation program [2], as a Stereolithography (STL) file format, as shown in Fig. 5. Then, the processor divides workpiece into small cubes using enmeshment function. The next step is to define material and injection parameters. In this work, natural rubber NR-40 is used as a specimen. There are significant empirical variables to input in the temperature-dependent rubber material properties such as density, heat conductivity, heat capacity, curing rate, and viscosity as a function of shear rate. Then, mold temperature for mold is set at 160 ºC. In addition, the temperature-conduction parameters of workpiece and mold were chosen to be 350 and 10000 W/m2K for Part to Mold and Mold to Mold, respectively. The injection time interval for one cycle can be divided into five intervals; lead time, filling time, movable time, movable part, fix part, and part take out as shown in Fig. 6. The controlled parameters are also shown in Fig. 7. Finally, the operating mold pressure, gating and heater positions are included.

Fig. 5. The STL file for both for core and cavity plates.

R. Panyawipart, S. Rodkwan and C. Raksiri

ASV0056-003-4 9th Asian Symposium on Visualization, Hong Kong SAR, China, 2007.

Fig. 6. Time interval for injection simulation process.

Fig. 7. Control parameters.

3. Results and Discussions A comparison of empirical and simulation work of rubber injection on a two cavities testing is shown in Table 1. In this table, the stroke of injection machine is varied from 25 to 120 mm. It can be seen that the simulated results correlate well with the injection testing in terms of deformed shape. However, the injection pressure result did not agree very well due to the element segmentation of the workpiece during simulation. Additional, the rubber characteristic curve, especially, a viscosity curve, defined previously during the material input can cause the overpressure results compare with an experiment. Fig. 8. shows the air contact time between rubber and air. The air trap or unfilling can be existed on the surface of the area which has a maximum air contact. The filled time of rubber injection is shown in Fig. 9. This leads to the position of rubber material entering the mold at each stage. Fig. 10 shows the flow length which describes the path of rubber flowing from the gate. The high flow length can result in pressure drop in the mold section, and material age is depicted in Fig. 11. This can relate to the overcured status of rubber in the mold. The wall contact time, a time that rubber is attached to the wall of the mold, is shown in Fig. 12. Weldline is also shown in Fig. 13. In this work, the weldline can not be seen clearly. Tracers of rubber particle which shows the distribution of rubber particle, can be displayed. In addition, the injection temperature is shown in Fig. 14. Even though higher injection temperature can result in the reduced cycle time, it can lead to the overcured rubber.

A Simulation and Optimization of Rubber Injection Molding Process

ASV0056-003-5 9th Asian Symposium on Visualization, Hong Kong SAR, China, 2007.

Fig. 8. (left) The air contact time between rubber and air. Fig. 9. (middle) Filled time of rubber injection.

Fig. 10. (right) Flow length of rubber. Table 1 Comparison of empirical and simulated injection shape and pressure results.

Stroke Simulation Injection Testing

25 mm

Injection Pressure 1298 bar Injection Time 1.03 seconds

Injection Pressure 777 bar

Injection Time 1.02 seconds

40 mm

Injection Pressure 1300 bar Injection Time 1.50 seconds

Injection Pressure 858 bar Injection Time 1.49 seconds

50 mm

Injection Pressure 1300 bar Injection Time 1.80 seconds

Injection Pressure 840 bar

Injection Time 1.83 seconds

75 mm

Injection Pressure 1307 bar Injection Time 2.70 seconds

Injection Pressure 865 bar

Injection Time 2.69 seconds

R. Panyawipart, S. Rodkwan and C. Raksiri

ASV0056-003-6 9th Asian Symposium on Visualization, Hong Kong SAR, China, 2007.

Stroke Simulation Injection Testing

90 mm

Injection Pressure 1315 bar Injection Time 3.20 seconds

Injection Pressure 918 bar

Injection Time 3.18 seconds

120 mm

Injection Pressure 1326 bar Injection Time 3.43 seconds

Injection Pressure 911 bar

Injection Time 4.19 seconds

Fig. 11. (left) Rubber age. Fig. 12. (middle) Wall contact time. Fig. 13. (right) Weldline of rubber.

Fig . 14. Injection temperature at 25%, 50%, 75% and 100%.

4. Conclusions

A Simulation and Optimization of Rubber Injection Molding Process

ASV0056-003-7 9th Asian Symposium on Visualization, Hong Kong SAR, China, 2007.

In this research, the application of CAE in rubber injection process was performed. Various output variables such as air contact time, filled time, flow length, material age, wall contact time, weldline, tracers, and injection temperature can be identified. The numerical results are also correlated relatively well with the empirical data using the rubber injection machine. This leads to the potential of using CAE application as a numerical tool to obtain the optimal conditions in rubber injection molding in the near future. References [1] Wheelans, M. A., “Injection Molding of Rubber”, London, Butterworths. (1974). [2] “3D-SIGMA User’s Manual Version 4.4”, SIGMA Engineering GmbH, Aachen, Germany, (2005).