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        Experimental-based optimization of polymer injection molding process parameters using anfis-ga method

        Yanli Cao,Xi-ying Fan,Yong-huan Guo,Xin Liu,Chunxiao Li,Lulu Li 대한기계학회 2022 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.36 No.3

        Compared with ordinary injection-molded parts, the slender, cantilevered, and thin-walled plastic parts are harsh on the injection molding process conditions. For complexity and particularity, it is difficult to form such parts. It is also more likely to cause excessive warpage deformation, affecting the molding quality and performance. The automobile audio shell is a typical slender, cantilevered, thin-walled plastic part. When the mold structure and material are determined, optimizing its injection molding process is the most economical and effective method to manufacture the products with the optimum properties. In order to minimize the warpage deformation, the adaptive network based fuzzy inference system (ANFIS) and genetic algorithm (GA) were adopted to optimize the injection molding process parameters. In particular, considering the high-dimensional nonlinear relationship between the process parameters and the warpage, the ANFIS is constructed as the prediction model of the warpage. Then, the GA is used to globally optimize the prediction model to determine the optimal process parameters. The results show that the optimization method based on ANFIS-GA has a good performance. The warpage is reduced to 0.0925 mm while reduced by 88.25 %. The optimal injection molding process parameters are used for simulation and manufacture, verifying the effectiveness and reliability of the optimization method.

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        Microstructures and Fatigue Life of SnAgCu Solder Joints Bearing Nano-Al Particles in QFP Devices

        Liang Zhang,Xi-ying Fan,Yong-huan Guo,Cheng-wen He 대한금속·재료학회 2014 ELECTRONIC MATERIALS LETTERS Vol.10 No.3

        Microstructures and fatigue life of SnAgCu and SnAgCu bearing nano-Al particles in QFP (Quad flat package) devices were investigated, respectively. Results show that the addition of nano-Al particles into SnAgCu solder can refine the microstructures of matrix microstructure. Moreover, the nano-Al particles present in the solder matrix, act as obstacles which can create a back stress, resisting the motion of dislocations. In QFP device, it is found that the addition of nano-Al particles can increase the fatigue life by 32% compared with the SnAgCu solder joints during thermal cycling loading.

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