An Effective Shrinkage Control Method for Tooth Profile Accuracy Improvement of Micro-Injection-Molded Small-Module Plastic Gears

Abstract

An effective method to control the non-linear shrinkage of micro-injection molded small-module plastic gears by combining multi-objective optimization with Moldflow simulation is proposed. The accuracy of the simulation model was verified in a micro-injection molding experiment using reference process parameters. The maximum shrinkage (Y1), volume shrinkage (Y2), addendum diameter shrinkage (Y3), and root circle diameter shrinkage (Y4) were utilized as optimization objectives to characterize the non-linear shrinkage of the studied gear. An analysis of the relationship between key process parameters and the optimization objectives was undertaken using a second-order response surface model (RSM-Quadratic). Finally, multi-objective optimization was carried out using the non-dominated sorting genetic algorithm-II (NSGA-II). The error rates for the key shrinkage dimensions were all below 2%. The simulation results showed that the gear shrinkage variables, Y1, Y2, Y3, and Y4, were reduced by 5.60%, 8.23%, 11.71%, and 11.39%, respectively. Moreover, the tooth profile inclination deviation (fHαT), the profile deviation (ffαT), and the total tooth profile deviation (FαT) were reduced by 47.57%, 23.43%, and 49.96%, respectively. Consequently, the proposed method has considerable potential for application in the high-precision and high-efficiency manufacture of small-module plastic gears.

Advanced Injection Molding Methods: Review

“…Studies showed that the use of the microinjection method for PDO processing makes it possible to obtain samples with high uniformity and shape stability [164]. The technique was also proven excellent in the high-precision and high-performance fabrication of small-module plastic gears [165]. Subsequently, Lin et al used µIM to fabricate light guiding plates (LGPs) as parts of liquid crystal displays [166].…”

Optimization of the Reduction of Shrinkage and Warpage for Plastic Parts in the Injection Molding Process by Extended Adaptive Weighted Summation Method

“…Optimization methods have evolved over the years. This development has moved from the trial and error method through the development of analytical calculations to the use of statistical models and the use of more advanced techniques such as second-order mathematical models and the use of artificial intelligence [ 16 , 17 , 18 , 19 ]. These models consider using existing plant equipment or specialized Engineering Add Computer (CAE) software such as Moldflow ® [ 20 ].…”

Optimization of Polyacrylic Acid Coating on Graphene Oxide-Functionalized Reverse-Osmosis Membrane Using UV Radiation through Response Surface Methodology

“…The results showed that the air gasification process yields 42.68% and 89.58% hydrogen and energy efficiencies at optimum conditions, respectively, while these values were higher for steam gasification, i.e., 64.02% for hydrogen and 96.52% for energy efficiency [14]. Similarly, other researchers used RSM to optimize printing parameters of sintered 316 L stainless steel [15], manufacturing of small-module plastic gears [16], a system based on biomass-fueled solid oxide fuel cell [17], solid polymer electrolyte-based technique for the electrochemical treatment of wastewater [18], and decolorization of congo red solution using iron-doped zinc oxide nanoparticles [19].…”