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Multi-Objective Optimizations for Microinjection Molding Process Parameters of Biodegradable Polymer Stent.
Hongxia Li1, Kui Liu2, Danyang Zhao3
1School of Mechanical Engineering, Dalian University of Technology, Dalian 116023, China. hxli@dlut.edu.cn.
This study introduces an adaptive optimization method using kriging surrogate models to improve polymer stent manufacturing. The method effectively reduces residual stress and warpage in microinjection molding processes.
Area of Science:
- Biomaterials Engineering
- Polymer Science
- Manufacturing Technology
Background:
- Microinjection molding of degradable polymer stents shows promise but faces challenges in optimizing process parameters for quality.
- Complex relationships between process parameters and molding quality hinder achieving optimal stent properties, specifically low residual stress and minimal warpage.
Purpose of the Study:
- To propose and validate an adaptive optimization method utilizing kriging surrogate models to minimize residual stress and warpage in polymer stent microinjection molding.
- To establish an efficient approach for determining optimal process parameters in polymer stent manufacturing.
Main Methods:
- An adaptive optimization strategy integrating design of experiment (DOE) and kriging surrogate models was developed.
- The kriging surrogate model approximates the relationship between process parameters and stent quality metrics (residual stress, warpage).
- Finite element method (FEM) simulations were employed to analyze the microinjection molding process, with expected improvement (EI) guiding the optimization search.
Main Results:
- The proposed method effectively reduced residual stress and warpage in the microinjection molding of a polymer vascular stent (ART18Z).
- The integration of DOE and kriging surrogate models provided an efficient alternative to computationally expensive reanalysis.
- Numerical results confirmed the capability of the adaptive optimization method in enhancing stent molding quality.
Conclusions:
- The adaptive optimization method based on kriging surrogate models is a viable and effective approach for improving the quality of microinjection molded polymer stents.
- This technique offers a significant advantage in optimizing complex manufacturing processes by reducing computational cost and improving defect control.
- The study demonstrates a pathway to enhance the development and production of high-quality degradable polymer stents for medical applications.
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