A study of gate location optimization of plastic injection molding using sequential linear programming

2009 ◽  
Vol 49 (1-4) ◽  
pp. 97-103 ◽  
Author(s):  
Ming Zhai ◽  
Ying Xie
Keyword(s):  
Linear Programming ◽  
Injection Molding ◽  
Plastic Injection Molding ◽  
Sequential Linear Programming ◽  
Location Optimization ◽  
Gate Location ◽  
Plastic Injection

Automated Selection of Gate Location for Plastic Injection Molding Processing

2005 ◽  
Vol 44 (2) ◽  
pp. 229-242 ◽  
Author(s):  
Ming Zhai ◽  
Y.C. Lam* ◽  
C.K. Au ◽  
D.S. Liu
Keyword(s):  
Injection Molding ◽  
Plastic Injection Molding ◽  
Gate Location ◽  
Plastic Injection ◽  
Selection Of

The Application of Improved Genetic Algorithm in Gate Location Optimization of Plastic Injection Molding

2013 ◽  
Vol 694-697 ◽  
pp. 2721-2724
Author(s):  
Xi Chen ◽  
Xi Cheng Wang
Keyword(s):  
Genetic Algorithm ◽  
Injection Molding ◽  
Optimal Solution ◽  
Plastic Injection Molding ◽  
Improved Genetic Algorithm ◽  
Gate Location ◽  
Design Variables ◽  
Population Genetic Algorithm ◽  
Plastic Injection ◽  
Species Equation

A multi-population genetic algorithm based on species equation and Kriging operator is presented in this paper. The parameters of species equation are considered as design variables and processed by real coding, the equation is regarded as modified arithmetic crossover operator to participate in genetic operation. The Kriging operator is bought in to enhance the ability of search optimal solution and promote convergence. The improved genetic algorithm, combined with Z-MOLD simulation program, is used to search the optimal gate location. The results show that the algorithm can effectively solve the plastic injection molding problem.

scholarly journals Energy and Eco-Impact Evaluation of Fused Deposition Modeling and Injection Molding of Polylactic Acid

2021 ◽  
Vol 13 (4) ◽  
pp. 1875
Author(s):  
Emmanuel Ugo Enemuoh ◽  
Venkata Gireesh Menta ◽  
Abdulaziz Abutunis ◽  
Sean O’Brien ◽  
Labiba Imtiaz Kaya ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Injection Molding ◽  
Polylactic Acid ◽  
Fused Deposition Modeling ◽  
Plastic Injection Molding ◽  
Measurement Models ◽  
Fused Deposition ◽  
Dog Bone ◽  
Deposition Modeling ◽  
Plastic Injection

There is limited knowledge about energy and carbon emission performance comparison between additive fused deposition modeling (FDM) and consolidation plastic injection molding (PIM) forming techniques, despite their recent high industrial applications such as tools and fixtures. In this study, developed empirical models focus on the production phase of the polylactic acid (PLA) thermoplastic polyester life cycle while using FDM and PIM processes to produce American Society for Testing and Materials (ASTM) D638 Type IV dog bone samples to compare their energy consumption and eco-impact. It was established that energy consumption by the FDM layer creation phase dominated the filament extrusion and PLA pellet production phases, with, overwhelmingly, 99% of the total energy consumption in the three production phases combined. During FDM PLA production, about 95.5% of energy consumption was seen during actual FDM part building. This means that the FDM process parameters such as infill percentage, layer thickness, and printing speed can be optimized to significantly improve the energy consumption of the FDM process. Furthermore, plastic injection molding consumed about 38.2% less energy and produced less carbon emissions per one kilogram of PLA formed parts compared to the FDM process. The developed functional unit measurement models can be employed in setting sustainable manufacturing goals for PLA production.

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