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1、AbstractThe quality of an injection molded part is largely affected by the mold cooling. Consequently, this makes it necessary to optimize the mold cooling circuit when designing the part but prior to designing the mold. Various approaches of optimizing the mold cooling circuit have been proposed pr

2、eviously. In this work, optimization of the mold cooling circuit was automated by a commercial process integration and design optimization tool called Process Integration, Automation andOptimization （PIAnO）, which is often used for large automotive parts such as bumpers and instrument panels. The co

3、oling channels and baffle tubes were located on the offset profile equidistant from the part surface. The locations of the cooling channels and the baffle tubes were automatically generated and input into the mold cooling computer-aided engineering program, Autodesk Moldflow Insight 2010. The object

4、ive function was the deviation of the mold surface temperature from a given design temperature. Design variables in the optimization were the depths, distances and diameters of the cooling channels and the baffle tubes. For a more practical analysis, the pressure drop and temperature drop were consi

5、dered the limited values. Optimization was performed using the progressive quadratic response surface method. The optimization resulted in a more uniform temperature distribution when compared to the initial design, and utilizing the proposed optimization method, a satisfactory solution could be mad

6、e at a lower cost.Key words : Injection molding, Cooling channel, Cooling analysis, PQRSM, Design optimization1. IntroductionThe cooling stage is the longest stage during the cycle time of the injection molding process. Therefore, the most effective method to reduce the cycle time is to reduce the c

7、ooling time. The cooling time is fundamentally determined by the part thickness and mold temperature, which creates a cooling time limitation. If the mold temperature and part thickness are uniform over a whole part, the cooling time is not a concern; however, non-uniform part thickness and mold tem

8、perature distribution lengthen the overall cooling time. A longer cooling time means poor temperature uniformity, which can cause the part to warp. This is especially true for large products, such as automotive bumpers and instrument panels. It is for these types of parts that temperature uniformity

9、 becomes the most important factor in mold design. We developed an automated optimization of the cooling circuit for an early part design in order to check the design validity. Usually the early part design is checked by the filing/packing and warpage analyses without a cooling analysis. This is bec

10、ause the assumption is that the mold temperature is uniform, which is not actually true.Providing a rapidly optimized cooling circuit for the designed part would help part designers correct their designThe optimization was designed to minimize the part temperature deviation using design variables su

11、ch as the diameters and distances of the cooling channels and baffle tubes and the depths of the part from the mold surface of the cooling channels and baffle tubes. A commercial computeraided engineering （CAE） tool, Autodesk Moldflow Insight, was used for the cooling analysis. We successfully obtai

12、ned an optimized cooling circuit in a time much shorter than can be achieved in a manual design. In order to develop the automated optimization of the cooling circuit for the practical mold design, practical design parameters such as the pressure drop limit and the coolant temperature rise were cons

13、idered in the optimization. The performance of the optimization technique can be affected by numerical noise in the responses. To find an optimum solution effectively when numerical noise exists, we performed an optimization by applying a regressionbased sequential approximate optimizer known as the

14、 Progressive Quadratic Response Surface Method （PQRSM）（Hong et al., 2000）, which was part of a commercial process integration and design optimization （PIDO） tool known as the Process Integration, Automation andOptimization （PIAnO） （FRAMAX,2009）. Figure 1. Finite element model of the product used for

15、 the optimization.2. MODEL AND CHANNEL CONFIGURATION 2.1. Model Configuration The model used for the optimization and CAE analysis was an automotive front bumper （FB）. The size of the part was1,800600 mm, the element type was triangular and then umber of elements in the model was approximately26,000

16、, with an average aspect ratio of 1.5. The model is shown in Figure 1. 2.2. Cooling Channel Configuration The cooling circuit for the automotive bumper mold is typically designed to have a horizontal plane of lin e cooling channels and to install baffle tubes from the line cooling channels. However, in this design, unnecessarily long baffle tubes attache