Startseite Multi-objective optimization of injection-molded plastic parts using entropy weight, random forest, and genetic algorithm methods
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Multi-objective optimization of injection-molded plastic parts using entropy weight, random forest, and genetic algorithm methods

  • Yanli Cao , Xiying Fan EMAIL logo , Yonghuan Guo , Sai Li und Haiyue Huang
Veröffentlicht/Copyright: 9. April 2020
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Journal of Polymer Engineering
Aus der Zeitschrift Journal of Polymer Engineering Band 40 Heft 4

Abstract

The qualities of injection-molded parts are affected by process parameters. Warpage and volume shrinkage are two typical defects. Moreover, insufficient or excessively large clamping force also affects the quality of parts and the cost of the process. An experiment based on the orthogonal design was conducted to minimize the above defects. Moldflow software was used to simulate the injection process of each experiment. The entropy weight was used to determine the weight of each index, the comprehensive evaluation value was calculated, and multi-objective optimization was transformed into single-objective optimization. A regression model was established by the random forest (RF) algorithm. To further illustrate the reliability and accuracy of the model, back-propagation neural network and kriging models were taken as comparative algorithms. The results showed that the error of RF was the smallest and its performance was the best. Finally, genetic algorithm was used to search for the minimum of the regression model established by RF. The optimal parameters were found to improve the quality of plastic parts and reduce the energy consumption. The plastic parts manufactured by the optimal process parameters showed good quality and met the requirements of production.

Keywords: entropy weight; genetic algorithm; injection molding; multi-objective optimization; random forest

  1. Research funding: This research was financially supported by the National Natural Science Foundation of China (funder id: http://dx.doi.org/10.13039/501100001809, grant 51475220) and the Xuzhou City Science and Technology Plan Projects (grant KC18239).

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Received: 2019-10-23
Accepted: 2020-02-24
Published Online: 2020-04-09
Published in Print: 2020-04-28

©2020 Walter de Gruyter GmbH, Berlin/Boston

Artikel in diesem Heft

  1. Frontmatter
  2. Material properties
  3. Interface properties of carbon fiber reinforced cyanate/epoxy resin composites at cryogenic temperature
  4. A new method to calculate the surface haze
  5. Structure and properties of particles/rubber composites applied on functionally graded lapping and polishing plate
  6. Adhesive properties of bio-based epoxy resin reinforced by cellulose nanocrystal additives
  7. Preparation and assembly
  8. Encapsulation of anion-cation organo-montmorillonite in terpolymer microsphere: structure, morphology, and properties
  9. Preparation and characterization of chitosan grafted poly(lactic acid) films for biomedical composites
  10. Preparation and characterization of polyvinylpyrrolidone/cobalt ferrite functionalized chitosan graphene oxide (CoFe2O4@CS@GO-PVP) nanocomposite
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  12. Engineering and processing
  13. Multi-objective optimization of injection-molded plastic parts using entropy weight, random forest, and genetic algorithm methods
https://doi.org/10.1515/polyeng-2019-0326
Schlagwörter für diesen Artikel
entropy weight; genetic algorithm; injection molding; multi-objective optimization; random forest

Artikel in diesem Heft

  1. Frontmatter
  2. Material properties
  3. Interface properties of carbon fiber reinforced cyanate/epoxy resin composites at cryogenic temperature
  4. A new method to calculate the surface haze
  5. Structure and properties of particles/rubber composites applied on functionally graded lapping and polishing plate
  6. Adhesive properties of bio-based epoxy resin reinforced by cellulose nanocrystal additives
  7. Preparation and assembly
  8. Encapsulation of anion-cation organo-montmorillonite in terpolymer microsphere: structure, morphology, and properties
  9. Preparation and characterization of chitosan grafted poly(lactic acid) films for biomedical composites
  10. Preparation and characterization of polyvinylpyrrolidone/cobalt ferrite functionalized chitosan graphene oxide (CoFe2O4@CS@GO-PVP) nanocomposite
  11. Clay/(PEG-CMC) biocomposites as a novel delivery system for ibuprofen
  12. Engineering and processing
  13. Multi-objective optimization of injection-molded plastic parts using entropy weight, random forest, and genetic algorithm methods
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