A Methodology to Predict and Optimize Ease of Assembly for Injected Parts in a Family-Mold System

Abstract

In this study, the assembly behavior for two injected components made by a family mold system were investigated. Specifically, a feasible method was proposed to evaluate the characteristic length of two components within a family mold system using numerical simulation and experimental validation. Results show that as the packing pressure increases, the product index (characteristic length) becomes worse. This tendency was consistent for both the simulation prediction and experimental observation. However, for the same operation condition setting through a basic test, there were some differences in the product index between the simulation prediction and experimental observation. Specifically, the product index difference of the experimental observation was 1.65 times over that of the simulation prediction. To realize that difference between simulation and experiment, a driving force index (DFI) based on the injection pressure history curve was proposed. Through the DFI investigation, the internal driving force of the experimental system was shown to be 1.59 times over that of the simulation. The DFI was further used as the basis for machine calibration. Furthermore, after finishing machine calibration, the integrated CAE and DOE (called CAE-DOE) strategy can optimize the ease of assembly up to 20%. The result was validated by experimental observation.

Internal Gas-Assisted Mold Temperature Control for Improving the Filling Ability of Polyamide 6 + 30% Glass Fiber in the Micro-Injection Molding Process

“…This influence is more important in the micro-injection molding process, in which the melt flow length must be increased in the product’s micro-features. Because micro-injection molds are low cost and have the potential for high-volume production, they are used to manufacture a variety of polymer components in the injection molding field [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. Therefore, the most common applications of micro-injection molding are in micro-devices [ 9 , 10 ], optical structures [ 11 , 12 , 13 , 14 ], and micro-fluidic devices [ 15 , 16 , 17 ].…”