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1、外 文 翻 译毕业设计题目： SD2106鼻毛修剪器上下盖造型及模具设计 原文1： Single gate optimization for plastic injection mold* 译文1： 注塑模的单浇口优化 62Single gate optimization for plastic injection mold*Abstract: This paper deals with a methodology for single gate location optimization for plastic injection mold. The objective of the gat
2、e optimization is to minimize the warpage of injection molded parts, because warpage is a crucial quality issue for most injection molded parts while it is influenced greatly by the gate location. Feature warpage is defined as the ratio of maximum displacement on the feature surface to the projected
3、 length of the feature surface to describe part warpage. The optimization is combined with the numerical simulation technology to find the optimal gate location, in which the simulated annealing algorithm is used to search for the optimum. Finally, an example is discussed in the paper and it can be
4、concluded that the proposed method is effective.INTRODUCTIONPlastic injection molding is a widely used, complex but highly efficient technique for producing a large variety of plastic products, particularly those with high production requirement, tight tolerance, and complex shapes. The quality of i
5、njection molded parts is a function of plastic material, part geometry, mold structure and process conditions. The most important part of an injection mold basically is the following three sets of components: cavities, gates and runners, and cooling system.Lam and Seow (2000) and Jin and Lam (2002)
6、achieved cavity balancing by varying the wall thickness of the part. A balance filling process within the cavity gives an evenly distributed pressure and temperature which can drastically reduce the warpage of the part. But the cavity balancing is only one of the important influencing factors of par
7、t qualities. Especially, the part has its functional requirements, and its thicknesses should not be varied usually.From the pointview of the injection mold design, a gate is characterized by its size and location, and the runner system by the size and layout. The gate size and runner layout are usu
8、ally determined as constants. Relatively, gate locations and runner sizes are more flexible, which can be varied to influence the quality of the part. As a result, they are often the design parameters for optimization.Lee and Kim (1996a) optimized the sizes of runners and gates to balance runner sys
9、tem for multiple injection cavities. The runner balancing was described as the differences of entrance pressures for a multi-cavity mold with identical cavities, and as differences of pressures at the end of the melt flow path in each cavity for a family mold with different cavity volumes and geomet
10、ries. The methodology has shown uniform pressure distributions among the cavities during the entire molding cycle of multiple cavities mold.Zhai et al.(2005a) presented the two gate location optimization of one molding cavity by an efficient search method based on pressure gradient (PGSS), and subse
11、quently positioned weld lines to the desired locations by varying runner sizes for multi-gate parts (Zhai et al., 2006). As large-volume part, multiple gates are needed to shorten the maxiinjection pressure. The method is promising for design of gates and runners for a single cavity with multiple ga
12、tes.Many of injection molded parts are produced with one gate, whether in single cavity mold or in multiple cavities mold. Therefore, the gate location of a single gate is the most common design parameter for optimization. A shape analysis approach was presented by Courbebaisse and Garcia (2002), by
13、 which the best gate location of injection molding was estimated. Subsequently, they developed this methodology further and applied it to single gate location optimization of an L shape example (Courbebaisse, 2005). It is easy to use and not time-consuming, while it only serves the turning of simple
14、 flat parts with uniform thickness.Pandelidis and Zou (1990) presented the optimization of gate location, by indirect quality measures relevant to warpage and material degradation, which is represented as weighted sum of a temperature differential term, an over-pack term, and a frictional overheatin
15、g term. Warpage is influenced by the above factors, but the relationship between them is not clear. Therefore, the optimization effect is restricted by the determination of the weighting factors.Lee and Kim (1996b) developed an automated selection method of gate location, in which a set of initial g
16、ate locations were proposed by a designer and then the optimal gate was located by the adjacent node evaluation method. The conclusion to a great extent depends much on the human designers intuition, because the first step of the method is based on the designers proposition. So the result is to a larg
