Numerical Optimization of Biomechanical Devices Using Computational Intelligence: Applications in Biotechnology Innovation

Abstract

In the biotechnology sector, the design of biomechanical devices, such as prosthetics and biomedical equipment, requires a balance between strength, functionality, comfort, and efficiency. These devices often demand lightweight structures with optimized mechanical properties to meet the needs of users while adhering to high-performance standards. However, the lack of uniform design parameters presents a challenge for achieving consistent and reliable optimization. This study explores the application of computational intelligence methods for the numerical optimization of biomechanical devices, providing a comprehensive framework for efficient design. The research develops a digital optimization process that includes modeling, preprocessing, solving, post-processing, design modification, and verification. To address the high standards of biomechanical performance, the study applies the finite element method (FEM) to analyze and calculate device stiffness under conditions simulating real-world usage. Using the GMW14876 standard for vibration and noise (NVH) testing as a reference, the study evaluates biomechanical device performance. CATIA V5R28 software is utilized for modeling and simulation, and subsequent optimizations are made based on analysis results. The optimized design is further validated through physical testing to confirm the accuracy of the FEM-based predictions. The findings demonstrate the feasibility of the proposed computational intelligence-based optimization method. The approach significantly reduces research and development costs, shortens design cycles, and improves the mechanical performance of biomechanical devices. By providing a scalable and reliable framework, this study offers a pathway for advancing the design and development of biomechanical equipment in biotechnology, ensuring better outcomes for users and fostering innovation in the field.