Development of Design-Phase Digital Twin for Structural Optimization of a Biomedical Device

Area of Science:

• Biomedical Engineering
• Mechanical Engineering
• Materials Science

Background:

• Digital twin adoption in medical device development is limited compared to traditional engineering.
• Conventional build-and-test methods hinder design exploration and risk identification.
• Capsule-based biomedical delivery systems require robust mechanical interfaces for safe operation.

Purpose of the Study:

• To develop and validate a design-phase behavioral digital twin for a capsule-based biomedical delivery system.
• To integrate empirical testing, analytical theory, and Finite Element Analysis (FEA) for accurate modeling.
• To optimize a critical snap-fit interface for improved performance and manufacturability.

Main Methods:

• Developed a calibrated digital twin using empirical data, analytical snap-fit theory, and nonlinear FEA.
• Integrated physical testing with numerical simulations to validate the digital twin.
• Employed Taguchi orthogonal arrays for efficient design optimization under strain constraints.

Main Results:

• Achieved strong agreement between analytical, numerical, and empirical models, with prediction errors within experimental repeatability.
• Identified undercut depth as the primary factor influencing retention strength.
• Optimized design demonstrated a 65%-75% increase in mating force while maintaining strain limits, with predicted peak force of 190 N.

Conclusions:

• The validated digital twin enables predictive, manufacturability-aware design for biomedical devices.
• This approach shifts development from reactive validation to proactive risk mitigation.
• Enhanced design optimization strengthens patient safety, clinician confidence, and regulatory assurance for Class II medical devices.