【正文】 Single gate optimization for plastic injection mold Abstract: Abstract: This paper deals with a methodology for single gate location optimization for plastic injection mold. The objective of the gate 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 length of the feature surface to describe part warpage. The optimization is bined 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 concluded that the proposed method is effective. Key words: Injection mold, Gate location, Optimization, Feature warpage. INTRODUCTION Plastic injection molding is a widely used, plex but highly efficient technique for producing a large variety of plastic products, particularly those with high production requirement, tight tolerance, and plex shapes. The quality of injection 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 ponents: cavities, gates and runners, and cooling system. Lam and Seow (2020) and Jin and Lam (2020) achieved cavity balancing by varying the wall thick ness of the part. A balance filling process within the cavity gives an evenly distributed pressure and tem perature which can drastically reduce the warpage of the part. But the cavity bala ncing is only one of the important influencing factors of part qualities. Espe cially, 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 usually 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 pa rameters for optimization. Lee and Kim (1996a) optimized the sizes of runners and gates to balance runner system for mul tiple injection cavities. The runner balancing was described as the differences of entrance pressures for a multicavity mold with identical cavities, and as differences of pressures at the 1 end of the melt flow path in each cavity for a family mold with different cavity vo lumes and geometries. The methodology has shown uniform pressure distributions among the cavities during the entire molding cycle of multiple cavities mold. Zhai et al.(2020a) presented the two gate loca tion optimization of one molding cavity by an effi cient search method based on pressure gradient (PGSS), and subsequently positioned weld lines to the desired locations by varying runner sizes for multigate parts (Zhai et al., 2020). As largevolume part, multiple gates are needed to shorten the maxi mum flow path, with a corresponding decrease in injection pressure. The method is promising for de sign of gates and runners for a single cavity with multiple gates. 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 mon design parameter for optimization. A shape analysis approach was pre sented by Courbebaisse and Garcia (2020), by which the best gate location of injection molding was esti mated. Subsequently, they developed this methodol ogy further and applied it to single gate location op timization of an L shape example (Courbebaisse, 2020). It is easy to use and not timeconsuming, while it only serves the turning of simple flat parts with uniform thickness. Pandelidis and Zou (1990) presented the opti mization of gate location, by indirect quality measures relevant to warpage and material degradation, which is represented as weighted sum of a temperature dif ferential term, an overpack term, and a frictional overheating 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 gate 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 designer’s intuition, because the first step of the method is based on the designer’s proposition. So the result is to a large ex tent limited to the designer’s experience. Lam and Jin (2020) developed a gate location optimization method based on the minimization of the Standard Deviation of Flow Path Length (SD[L]) and Standard Deviation of Filling Time (SD[T]) during the molding filling process. Subsequently, Shen et al.(2020a。 2020b) optimized the gate location design by minimizing the weighted sum of filling pressure, filling time difference between different flow paths, temperature difference, and overpack percentage. Zhai et al.(2020b) investigated optimal gate location with evaluation criteria of injection pressure at the end of filling. These researchers presented the objec tive functions as 2 performances of injection molding filling operatio