A research method to improve the quality of box-type thin-walled parts by combining parameter optimization and i nverse-deformation design

Abstract

In this paper, a five-part study on the molding quality of box-type thin-walled injection molded parts with volume shrinkage and warpage deformation was conducted. In the first part, the molding parameters: filling time, plastic temperature, mold temperature (C), holding time (D), maximum holding pressure (E), and cooling time (F) were selected, and a six-factor, five-level L25 (5 6 ) orthogonal experimental design (OED) was designed. Then, the optimal combination of molding parameters was optimized by using gray correlation (GC) theory analysis. In the second part, the six molding parameters from the first part were further optimized based on the Box Behnken Design (BBD) response surface method (RSM) and BP neural network (BPNN) training, and the results showed that the fitted regression model after BPNN training had a smaller prediction error. In the third part, the regression models fitted with BBD and BPNN-BBD are further optimized globally. The optimization search method uses the NSGA-II genetic optimization algorithm. And comparing the above four optimization methods found that BPNN-BBD-NSGA-II prediction error < BPNN-BBD prediction error < BBD-NSGA-II prediction error < BBD prediction error. The fourth part is based on the anti-deformation design (ADD) theory. The NX/Moldex3D global optimization platform is created to finally almost completely eliminate warpage deformation of box-type thin-walled injection molded parts. In the last part, a trial mold verification analysis was performed, and the molding quality data was obtained by using optical scanning instruments, and the GOM software was used to compare and analyze the deviation values of each appearance surface and the flatness values.

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

“…This paper presents a modification of the WSM presented by [ 28 ] by considering the restriction of the variables in order to obtain an optimal point and reduce the shrinkage and warpage in the plastic injection process. Regarding the plastic injection molding process, different works use Pareto optimization to optimize the parameters of the injection molding process to optimize the quality of the parts in order to reduce manufacturing costs [ 29 , 30 , 31 ].…”

Comparison of Numerical Methods for Geometric Warpage Compensation

“…In each iteration, the cavity geometry is adjusted in the opposite direction of the disparity between the current deformed geometry and the ideal geometry. This method is inspired by experimental cavity shape compensation, where discrete measurements of produced parts inform adjustments [18,19,24]. However, this so-called reverse geometry method [25] requires identical meshes with corresponding nodes for both the deformed and ideal shapes.…”

“…In this approach, the produced part from the modified cavity shape still undergoes warpage, but it ultimately attains the desired shape after deformation [17]. While this method can be implemented through iterative experiments, every time measuring the newly produced part and adjusting the cavity accordingly, this proves to be both costly and time-consuming [18,19]. As an alternative, several simulation-based numerical methods have been suggested to calculate the optimal geometry for the cavity shape.…”