A systematic approach to parameter selection for CAD-virtual reality data translation using response surface...

Area of Science:

• Computer-Aided Design (CAD)
• Virtual Reality (VR)
• Engineering Design Optimization

Background:

• Advanced graphics enable virtual reality (VR) for efficient design.
• Integrating CAD and VR software presents significant challenges.
• Existing methods struggle with seamless data transfer and model fidelity.

Purpose of the Study:

• To address impediments in integrating CAD and VR software.
• To develop and validate a methodology for optimizing VR model representation.
• To enhance graphics quality and design attributes in VR environments.

Main Methods:

• Empirical testing of selected conversion parameters for VR model generation.
• Statistical analysis including R-squared (pred) and R-squared (adjusted) for model validation.
• Utilizing optimization software (MODE Frontier) with Design of Experiments (DOE) for response surface analysis.

Main Results:

• A reduced model demonstrated significant response variability explanation (86.64% adjusted R-squared).
• Further model refinement improved predictive capability (73.32% pred R-squared, 79.49% adjusted R-squared).
• Optimized parameter values yielded superior graphics quality and design attributes.

Conclusions:

• The proposed experimental design methodology effectively enhances VR model quality for CAD integration.
• Optimized conversion parameters are crucial for achieving high-fidelity VR design experiences.
• This approach facilitates more efficient and effective use of VR in the design phase.