Multi-criteria optimization of polymer selection for biomedical additive manufacturing using analytic hierarchy process

Abstract

This study presents a novel material design framework that integrates multi-criteria decision analysis with systematic property evaluation to guide the development of application-specific polymeric materials for biomedical applications. Using the Analytic Hierarchy Process (AHP), the study established quantitative relationships between material properties and biomedical performance requirements across five thermoplastic polymers (ABS, PLA, PC, PETG, and Nylon). The framework identifies critical design parameters including biocompatibility (25.6 %), stimuli response (16.4 %), and mechanical properties (15.5 %) that drive material performance in biomedical applications. Our analysis reveals that PLA’s molecular structure and processing characteristics contribute to superior overall performance (28.66 %), while PC’s aromatic backbone provides exceptional mechanical strength (25.98 %) and Nylon’s polyamide chains enable unique environmental responsiveness (22.40 %). The validated framework (CR = 0.084) demonstrates how material chemistry and processing parameters can be optimized for specific biomedical applications. Monte Carlo simulation confirms the robustness of structure–property relationships, with PLA maintaining design superiority in 84.3 % of scenarios. This work establishes a materials design methodology that connects molecular structure, processing parameters, and end-use performance, providing a foundation for developing next-generation polymeric materials tailored for biomedical additive manufacturing applications.

Keywords

• Additive manufacturing
• Analytic hierarchy process
• Biomedical applications
• Fused deposition modeling
• Multi-criteria decision making
• Polymer selection