Cargando…

Multi-Objective Optimizations for Microinjection Molding Process Parameters of Biodegradable Polymer Stent

Microinjection molding technology for degradable polymer stents has good development potential. However, there is a very complicated relationship between molding quality and process parameters of microinjection, and it is hard to determine the best combination of process parameters to optimize the m...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Hongxia, Liu, Kui, Zhao, Danyang, Wang, Minjie, Li, Qian, Hou, Jianhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6267175/
https://www.ncbi.nlm.nih.gov/pubmed/30463214
http://dx.doi.org/10.3390/ma11112322
_version_ 1783376006949634048
author Li, Hongxia
Liu, Kui
Zhao, Danyang
Wang, Minjie
Li, Qian
Hou, Jianhua
author_facet Li, Hongxia
Liu, Kui
Zhao, Danyang
Wang, Minjie
Li, Qian
Hou, Jianhua
author_sort Li, Hongxia
collection PubMed
description Microinjection molding technology for degradable polymer stents has good development potential. However, there is a very complicated relationship between molding quality and process parameters of microinjection, and it is hard to determine the best combination of process parameters to optimize the molding quality of polymer stent. In this study, an adaptive optimization method based on the kriging surrogate model is proposed to reduce the residual stress and warpage of stent during its injection molding. Integrating design of experiment (DOE) methods with the kriging surrogate model can approximate the functional relationship between design goals and design variables, replacing the expensive reanalysis of the stent residual stress and warpage during the optimization process. In this proposed optimization algorithm, expected improvement (EI) is used to balance local and global search. The finite element method (FEM) is used to simulate the micro-injection molding process of polymer stent. As an example, a typical polymer vascular stent ART18Z was studied, where four key process parameters are selected to be the design variables. Numerical results demonstrate that the proposed adaptive optimization method can effectively decrease the residual stress and warpage during the stent injection molding process.
format Online
Article
Text
id pubmed-6267175
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-62671752018-12-17 Multi-Objective Optimizations for Microinjection Molding Process Parameters of Biodegradable Polymer Stent Li, Hongxia Liu, Kui Zhao, Danyang Wang, Minjie Li, Qian Hou, Jianhua Materials (Basel) Article Microinjection molding technology for degradable polymer stents has good development potential. However, there is a very complicated relationship between molding quality and process parameters of microinjection, and it is hard to determine the best combination of process parameters to optimize the molding quality of polymer stent. In this study, an adaptive optimization method based on the kriging surrogate model is proposed to reduce the residual stress and warpage of stent during its injection molding. Integrating design of experiment (DOE) methods with the kriging surrogate model can approximate the functional relationship between design goals and design variables, replacing the expensive reanalysis of the stent residual stress and warpage during the optimization process. In this proposed optimization algorithm, expected improvement (EI) is used to balance local and global search. The finite element method (FEM) is used to simulate the micro-injection molding process of polymer stent. As an example, a typical polymer vascular stent ART18Z was studied, where four key process parameters are selected to be the design variables. Numerical results demonstrate that the proposed adaptive optimization method can effectively decrease the residual stress and warpage during the stent injection molding process. MDPI 2018-11-19 /pmc/articles/PMC6267175/ /pubmed/30463214 http://dx.doi.org/10.3390/ma11112322 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Hongxia
Liu, Kui
Zhao, Danyang
Wang, Minjie
Li, Qian
Hou, Jianhua
Multi-Objective Optimizations for Microinjection Molding Process Parameters of Biodegradable Polymer Stent
title Multi-Objective Optimizations for Microinjection Molding Process Parameters of Biodegradable Polymer Stent
title_full Multi-Objective Optimizations for Microinjection Molding Process Parameters of Biodegradable Polymer Stent
title_fullStr Multi-Objective Optimizations for Microinjection Molding Process Parameters of Biodegradable Polymer Stent
title_full_unstemmed Multi-Objective Optimizations for Microinjection Molding Process Parameters of Biodegradable Polymer Stent
title_short Multi-Objective Optimizations for Microinjection Molding Process Parameters of Biodegradable Polymer Stent
title_sort multi-objective optimizations for microinjection molding process parameters of biodegradable polymer stent
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6267175/
https://www.ncbi.nlm.nih.gov/pubmed/30463214
http://dx.doi.org/10.3390/ma11112322
work_keys_str_mv AT lihongxia multiobjectiveoptimizationsformicroinjectionmoldingprocessparametersofbiodegradablepolymerstent
AT liukui multiobjectiveoptimizationsformicroinjectionmoldingprocessparametersofbiodegradablepolymerstent
AT zhaodanyang multiobjectiveoptimizationsformicroinjectionmoldingprocessparametersofbiodegradablepolymerstent
AT wangminjie multiobjectiveoptimizationsformicroinjectionmoldingprocessparametersofbiodegradablepolymerstent
AT liqian multiobjectiveoptimizationsformicroinjectionmoldingprocessparametersofbiodegradablepolymerstent
AT houjianhua multiobjectiveoptimizationsformicroinjectionmoldingprocessparametersofbiodegradablepolymerstent