For a plastic diffusion lens to uniformly diffuse light, it is important to minimize deformation that may occur during injection molding and to minimize deformation. It is essential to control the injection molding condition precisely. In addition, as the number of meshes increases, there is a limitation in that the time required for analysis increases. Therefore, We applied machine learning algorithms for faster and more precise control of molding conditions. This study attempts to predict the deformation of a plastic diffusion lens using the Decision Tree regression algorithm. As the variables of injection molding, melt temperature, packing pressure, packing time, and ram speed were set as variables, and the dependent variable was set as the deformation value. A total of 256 injection molding analyses were conducted. We evaluated the prediction model's performance after learning the Decision Tree regression model based on the result data of 256 injection molding analyses. In addition, We confirmed the prediction model's reliability by comparing the injection molding analysis results.

The cooling process in the injection molding requires the longest time. Therefore, a lot of studies have been conducted to reduce the cooling time. In particular, studies on conformal cooling channels using 3D printing are actively being conducted. In this study, the effect of the conformal cooling channel considering the hood shape instead of the conventional linear cooling channel was investigated by injection molding analysis. In the analysis results, when the conformal cooling channel was applied, the length deformation of the molded product was reduced by about 33% and the circular deformation of the hood assembled on the lens was reduced by about 7.1㎛.

Smart phones are currently the most popular electronic devices with high volume production activities driven by high demand and requirements for rapid turnaround time. The changes of displacement were analyzed according to a variable of the gate size and runner system. The radial type and gate with large size were shown that better results in displacement. While the design and production of lenses, the key component of a camera, still need to be improved, the current technology has run into its limit with regard to trends in size and weight reduction. In this study, an injection molding analysis was performed on plastic lenses that are widely employed for smart phone cameras. Specifically, the displacement of lenses at the time of injection molding was studied by varying the gate size and runner system.