The hybrid approach of genetic algorithm and particle swarm optimization on reduced weld line defect in plastic injection molding

被引:0
作者
Oktem, Hasan [1 ,2 ]
Uygur, Ilyas [3 ]
Sari, Ece Simooglu [1 ]
Shinde, Dinesh [4 ]
机构
[1] Kocaeli Univ, Hereke Asim Kocabiyik Vocat Sch, Dept Machine & Met Technol, Agah Ates St, TR-41380 Kocaeli, Turkiye
[2] Kocaeli Univ, Nat Sci Inst Polymer Sci & Technol, Umuttepe, Turkiye
[3] Duzce Univ, Dept Mech Engn, Duzce, Turkiye
[4] Elecon Gear Co, Anand, Gujarat, India
关键词
Plastic injection molding; process conditions; analysis of variance; parametric analysis; genetic algorithm; particle swarm optimization; PROCESS PARAMETER OPTIMIZATION; MECHANICAL-PROPERTIES; MICROSTRUCTURE; WELDLINES;
D O I
10.1177/14777606241270516
中图分类号
TB33 [复合材料];
学科分类号
摘要
Weld lines are a serious defect observed in plastic injection molded parts, impacting both their cosmetic appearance and mechanical properties. Controlling the conditions of plastic injection is crucial to mitigate these weld lines. This study introduces a novel approach to identify polypropylene injection molding (PIM) conditions aimed at reducing weld lines in polypropylene parts. The PIM conditions considered in this study include melt temperature, injection pressure, packing pressure, packing time, and cooling time. An orthogonal array Taguchi L27 design was employed for the experimental setup, producing 27 polypropylene parts with varying combinations of process conditions. The width of weld lines generated on the parts' surfaces was measured using an optimum microscope for all trials. Parametric analysis was conducted using response surface plots and contour plots to estimate the process conditions yielding minimum weld lines. Analysis of variance and regression analysis were employed to interpret the experimental data, with the resulting regression equation used to predict weld lines for a set of PIM process conditions. Finally, two efficient optimization algorithms, genetic algorithm (GA), and particle swarm optimization (PSO), were implemented using MATLAB programming to estimate the optimum process conditions for minimizing weld lines. The GA and PSO predicted weld line widths of 6.12302 mu m and 6.123 mu m, respectively, representing an 18.51% improvement in results. These findings demonstrate that the novel approach presented in this study can be effectively and reliably applied to address plastic product defects in the industry.
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页数:16
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