Multi-Objective Optimization of an Injection Molding Process for an Alvarez Freeform Lens Using an Integrated Optical...

Area of Science:

• Optical Engineering
• Manufacturing Science
• Computational Modeling

Background:

• Alvarez freeform lenses offer unique optical properties but present manufacturing challenges.
• Optimizing injection molding parameters is crucial for achieving desired lens quality.
• Integrating design and manufacturing simulations is complex due to data conversion issues.

Purpose of the Study:

• To optimize the design and fabrication of injection-molded Alvarez freeform lenses.
• To address conversion issues between manufacturing and optical design simulations.
• To compare the effectiveness of Gray Relational Analysis (GRA) and Robust Multi-Criteria Optimization (RMCO) for parameter optimization.

Main Methods:

• Utilized Moldex3D for mold flow analysis and CODE V for optical design simulations.
• Employed Taguchi design methodology to identify key injection molding parameters affecting lens quality.
• Applied GRA and RMCO to determine optimal injection molding parameters for enhanced optical performance.

Main Results:

• The integrated dual-software approach successfully facilitated seamless transitions between simulation modules.
• Taguchi method identified critical parameters influencing lens quality.
• RMCO demonstrated superior performance over GRA in improving lens optical quality metrics like spot diagram, distortion, and MTF.

Conclusions:

• The proposed integrated method combining Moldex3D, CODE V, Taguchi, and RMCO is effective for optimizing Alvarez freeform lens injection molding.
• RMCO provides more substantial improvements in optical quality compared to GRA.
• This methodology can be extended to optimize other optical components and systems.