Thin-wall plastic part injection molding process parameter multi-objective optimization method

A technology of multi-objective optimization and process parameters, which is applied in the field of process parameter optimization and multi-objective optimization of thin-walled plastic injection molding process parameters. Effect

Pending Publication Date: 2020-12-18
XUZHOU NORMAL UNIVERSITY
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  • Thin-wall plastic part injection molding process parameter multi-objective optimization method
  • Thin-wall plastic part injection molding process parameter multi-objective optimization method
  • Thin-wall plastic part injection molding process parameter multi-objective optimization method

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[0027] This multi-objective optimization method for injection molding process parameters of thin-walled plastic parts takes minimizing warpage and volume shrinkage as the two optimization objectives, and combines Moldflow simulation software with Latin hypercube sampling (LHS) to study different process parameters The influence of defects on plastic parts, and using Bayesian optimization improved random forest regression (BO-RFR) and non-dominated sorting genetic algorithm (Non-dominated sorting genetic algorithm II, NSGA-II) for multi-objective optimization. First, on the basis of LHS, random forest regression (RFR) is used to construct the mathematical relationship between the injection molding process parameters and the two optimization objectives; (Probability of improvement, PI) as the acquisition function, establish a Bayesian optimization algorithm (Bayesian optimization, BO), and use this to optimize the hyperparameters of RFR, so as to construct the BO-RFR model; final...

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Abstract

The invention discloses a thin-wall plastic part injection molding process parameter multi-objective optimization method, which takes minimum warping and volume shrinkage as two optimization objectives, combines Moldflow simulation software with Latin hypercube sampling LHS, and comprises the following steps of: firstly, constructing a mathematical relationship between injection molding process parameters and the two optimization objectives by adopting random forest regression RFR on the basis of the LHS; secondly, establishing a Bayesian optimization algorithm BO by taking a Gaussian processGP as a probability agent model and taking a lifting strategy PI as an acquisition function, and optimizing hyper-parameters of the RFR according to the Bayesian optimization algorithm BO so as to construct a BORFR model; finally, carrying out multi-objective optimization on the BORFR by adopting NSGAII to obtain optimal injection molding process parameters. Finite element simulation verificationand physical test verification show that the optimization method can greatly reduce the warping and volume shrinkage rate of the thin-wall plastic part.

Description

technical field [0001] The invention relates to a method for optimizing process parameters, in particular to a method for multi-objective optimization of process parameters for injection molding of thin-walled plastic parts based on BO-RFR and NSGA-II methods, and belongs to the technical field of injection molding. Background technique [0002] Plastic injection molding (PIM) is one of the most widely used processing techniques for producing plastic products to improve efficiency and manufacturability, with high production efficiency and processing capacity. PIM can effectively reduce product weight and promote the development of automobile lightweight. During the entire processing process, there are four main factors that affect the molding quality of the product, namely mold structure, part structure, molding material and process parameters. Compared with the other three factors, setting appropriate process parameters is the most direct and cost-effective method. The se...

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Application Information

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IPC IPC(8): G06Q10/04G06N3/12G06F30/27
CPCG06N3/126G06Q10/04G06F30/27
Inventor 曹艳丽范希营郭永环
Owner XUZHOU NORMAL UNIVERSITY
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