Multi-Objective Optimization of Injection Molding Parameters for Manufacturing Thin-Walled Composite Connector...

Area of Science:

• Materials Science
• Manufacturing Engineering
• Polymer Processing

Background:

• New energy vehicles require advanced connector structures.
• Thin-walled connectors face dimensional challenges like shrinkage and warping during injection molding.
• Optimizing injection molding is critical for connector performance.

Purpose of the Study:

• To optimize the injection molding process for thin-walled composite connectors.
• To address dimensional instability (shrinkage and warping) in these components.
• To improve the overall performance of injection-molded composite parts.

Main Methods:

• Utilized the Taguchi method for experimental design.
• Integrated grey relational analysis to handle multiple quality objectives.
• Fine-tuned key injection molding parameters: melt temperature, mold temperature, injection time, holding pressure/time, and cooling time.

Main Results:

• Successfully enhanced the injection molding process for thin-walled composite connectors.
• Achieved improved dimensional accuracy and reduced warping.
• Demonstrated a comprehensive framework for optimizing multi-objective molding processes.

Conclusions:

• The combined Taguchi and grey relational analysis approach is effective for optimizing complex molding processes.
• This method significantly improves the quality and performance of thin-walled composite connectors.
• The findings contribute to advancing manufacturing techniques for critical components in new energy vehicles.