This paper establishes a mathematical framework to assess the suitability of various biomaterials for orthopedic implants, addressing the challenge of a material selection problem. The study examines the stress and deformation experienced by the tibia bone during daily activities to determine the optimal material. The candidate materials under consideration are Ti6Al4V, magnesium alloy, and natural bone. For the analysis, the Taguchi L24 orthogonal array was employed to design the tests. The relative importance and contribution of each material to the responses were determined using analysis of variance (ANOVA). The results from the GRA indicate that Ti6Al4V is the most suitable material for orthopedic implants. In contrast, the Taguchi analysis identifies natural bone as the most suitable, followed by Ti6Al4V. Based on these findings, it can be concluded that Ti6Al4V is the best-suited material for orthopedic implants according to the optimization techniques employed in this study.

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Multi-objective Optimization of Biomaterials to Obtain Suitable Material for Orthopedic Implants

  • Omkar Raj Aryan,
  • Kishore Debnath

摘要

This paper establishes a mathematical framework to assess the suitability of various biomaterials for orthopedic implants, addressing the challenge of a material selection problem. The study examines the stress and deformation experienced by the tibia bone during daily activities to determine the optimal material. The candidate materials under consideration are Ti6Al4V, magnesium alloy, and natural bone. For the analysis, the Taguchi L24 orthogonal array was employed to design the tests. The relative importance and contribution of each material to the responses were determined using analysis of variance (ANOVA). The results from the GRA indicate that Ti6Al4V is the most suitable material for orthopedic implants. In contrast, the Taguchi analysis identifies natural bone as the most suitable, followed by Ti6Al4V. Based on these findings, it can be concluded that Ti6Al4V is the best-suited material for orthopedic implants according to the optimization techniques employed in this study.