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Runner system plays a very important role in injection molding process. A quality runner design is helpful in improving productqualities and saving material. However, traditional cold runner systems have certain inherent issues. Moreover, poor productcosmetics are commonly seen with the use of traditional cold runners. As a result, hot runner technology has been widely applied.On the other hand, It has been one of the green molding solutions for material/energy saving and clean environments. But themechanism behind the hot runner system is too complicated to be fully understood. There exist some critical issues currently. As aresult, the simulation technolgy is highly needed to examine hot runner designs before the real manufacturing. Through simulationanalyses, designers and manufafctuers are able to catch the potential issues on their hot runner systems and revise their designs. Hotrunner simulation technology helps with the investigations into the behavior in hot runner system. In this paper, a true 3D numericalmethod is proposed and applied to investigate the temperature behavior in a real hot runner system for PC material. The experimentis conducted and the simulating result is compared with that from the experiment for the validation purpose.27936
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1. IntroductionIn recent years, how to minimize the negative impact on theenvironment and to provide more sustainable product life cycle is oneof crucial considerations in design and manufacturing.1,2 In massproduction, plastic processing provides one of most feasible ways toconnect design to manufacturing. For plastic production, runner systemplays a very important role in injection molding process.3-5 The qualityrunner design is very helpful in improving product qualities.Traditional cold runner systems have certain inherent issues. As aresult, hot runner technology6-9 has become the trend in order to dealwith those cold runner issues in injection molding process.A hot runner system is mainly composed of hot runner gate, hotnozzle, manifold and heating coil. Since it is so complicated, themechanism is too difficult to be fully understood. In addition, thereexist some critical issues in the current hot runner technology, such astemperture control issues, flow imbalance, and material stagnation/degradation. As a result, a simulation technolgy is in great demand toexamine their designs before the real prodcution. Through simulationanalysis results, designers and manufafctuers are able to investigatetemperture profile, pressure drop, shear heating effect etc., and find the potential issues on their hot runner systems. Therefore, it can helpimprove hot runner system designs and product qualities.In this paper, a true 3D numerical method is proposed to simulatethe behavior of a real hot runner system for PC material. Through thenumerical simulation the dynamic melt temperature profile in the hotrunner system can be investigated. The injection molding experiment isconducted and the temperature is measured at the locations of interest.The simulating results are compared with those from the experiment tovalidate this simulation technology. The results indicate goodagreement both in trend and magnitude. The mechanism is alsodiscussed to explain how sensor node placement is critical for productquality and material saving.
2. Numerical Simulation2.1 Numerical TheoryA true 3D numerical method is developed and used to simulate thebehavior of hot runner systems. The CAE model can be created byusing Moldex3D®. A three-dimensional, cyclic, transient heatconduction problem with boundary/initial conditions on hot runner component surfaces is involved. The overall heat transfer phenomenonis governed by a three-dimensional Poisson equation.10-13 (1)where T is the temperature, t is the time, x, y, and z are the Cartesiancoordinates, ρ is the density, CP is the specific heat, k is the is thethermal conductivity, and q is heat source from the heating coils. Theeffect of thermal radiation is ignored here. The conditions defined overthe boundary surfaces and interfaces of the mold are specified as below,where n is the normal direction of mold boundary, h is heat transfercoefficient. On the exterior surfaces of the moldbase is air temperature. (2)(3)(4)where hair heat transfer coefficient is governed by the empirical NusseltNumber and Raleigh Number which govern the system.142.2 Model DescriptionThis system includes the part, hot runner nozzle, 3 sets of heatingcoils, 3 brass bushings which the heating coils are wrapped around, ametal mold, and other bushing components (see Fig. 1). The dimensionof the entire moldbase is 250.00 × 250.00 × 320.00 mm. The materialfor the metal mold is P20. The thermoplastic material for the melt is PC(Panlite L-1225Y). Fig. 1(b) indicates the materials used for each hotρCP∂T∂t------ k∂2T∂x2--------∂2T∂y2--------∂2T∂z2-------- ++⎝⎠⎜⎟⎛⎞qt () + =T 0 r , ()Tc ,Tp r () ⎩⎨⎧=for r Ωm ∈for r Ωp ∈for t 0 ,≥ km –∂T∂n------ hT To – () =hhair = T0 Tair = , for r Γm ∈ runner component. The component shown in the same color is made ofthe same material. Table 1 lists the material properties of density, heatcapacity and thermal conductivity for each hot runner components inthis system. These parameters are the inputs in the analysis to considerthe effects from different thermal properties.Fig. 2 shows the information of sensor node locations for heatingcoils and melt temperature measurement. The number 1 to 10 sensornodes are used to measure melt temperature function of time. Thenumber sensor nodes 1A, 2A, 3A, 1B, 2B, 3B, 1C are used to controlon/off for the heating coils. For each heating coil, it is traced andcontrolled by one sensor node. For example, for the 1st heating coil, itcan select the sensor node either in 1A, 1B, or 1C, but only one placeeach time. Similarly, it follows same way for 2nd and 3rd heating coilsas shown in Fig. 2. When the sensor nodes 1A, 2A, 3A are assigned toeach heating coils respectively, the target temperature is 280 and therange is ± 2oC. The power for each heating coil is 400 W or 610 W asindicated in figure 3. If the sensor node 1A reaches the temperature of282oC, the corresponding heating coil is switched off. On the contrary,if the temperature goes down to 278oC, the heating coil is turned on.This is the same way for dealing with other group setting.The filling time and packing time are both 5 seconds. The coolingchannel layout and coolant (water) temperature is also shown in Fig. 3.The cooling time and open time is 20s and 5s respectively. The cycletime is 35 seconds. The melt temperature on the sensor nodes 1 to 10can be predicted and compared with the experimental measurements.