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Liquid Silicone Rubber Headlamp Lens Injection Molding Process Optimization Based on Tie Bar Elongation and NSGA III
Hanjui Chang1,2, Shuzhou Lu1,2, Yue Sun1,2
1Department of Mechanical Engineering, College of Engineering, Shantou University, Shantou 515063, China.
Polymers
|November 14, 2023
Summary
Optimizing liquid silicone rubber lens injection molding with the NSGA-III algorithm significantly reduced residual stress by 47.14% and clamping force by 12.98%. This enhances lens quality and transmittance, providing a valuable guide for industrial processes.
Area of Science:
- Materials Science and Engineering
- Manufacturing Processes
- Polymer Processing
Background:
- Injection molding of Liquid Silicone Rubber (LSR) lenses presents challenges in achieving optimal quality due to complex process parameter interactions.
- Residual stress in LSR lenses can negatively impact optical performance and product integrity.
- Traditional optimization methods can be time-consuming for multi-objective problems in injection molding.
Purpose of the Study:
- To improve the injection molding quality of LSR material lenses by optimizing process parameters.
- To investigate the relationship between tie bar elongation, process parameters, and residual stress in LSR lenses.
- To reduce residual stress and enhance transmittance of LSR lenses through process optimization.
Main Methods:
- Utilized the Non-dominated Sorting Genetic Algorithm III (NSGA-III) for multi-objective optimization of injection molding parameters.
- Employed simulation software to analyze the injection molding process and the correlation between tie bar elongation and process parameters.
- Installed strain sensors on the tie bar to monitor clamping force and its relationship with lens residual stress.
Main Results:
- Optimized process parameters (melt temperature: 34.92 °C, holding pressure: 33.97 MPa, holding time: 9.96 s) were determined using NSGA-III.
- Optimized parameters resulted in a 12.98% reduction in clamping force and a 47.14% reduction in residual stress compared to initial parameters.
- Achieved an average transmittance of 95-98% for the manufactured LSR lenses, with predictable residual stress trends based on tie bar elongation.
Conclusions:
- The NSGA-III algorithm effectively optimizes injection molding parameters for LSR lenses, leading to significant reductions in residual stress and clamping force.
- Monitoring tie bar elongation provides a method for predicting residual stress trends in LSR lenses.
- The developed methodology enhances LSR lens quality, offering a practical approach for industrial injection molding process optimization.
