Publicação
Development of hybrid robotic-assisted technology for multifunctional biomedical implants customization
| Resumo: | This dissertation explores the development and implementation of a cutting-edge hybrid manufacturing (HM) system that integrates both additive and subtractive processes within a single robotic-assisted setup. This hybrid system addresses the inefficiencies and inaccuracies common in traditional manufacturing workflows, which often require the use of multiple machines and manual part transfers: issues particularly prevalent when producing complex, micro-scale, and biomedical components. By combining laser-based additive manufacturing (AM) with multi-axis CNC subtractive machining (SM), the system allows for the precise customization of intricate geometries and surface characteristics. A key innovation of this research lies in the integration of a unique nonplanar slicer, combined with inverse kinematics of a 7-axis robotic system (5-axis cnc + 2-axis galvo scan head), to effectively manage the complexities of curved surfaces. This innovative approach ensures highly accurate material removal and processing through laser, even on non-planar surfaces, a critical feature when customizing components for biomedical applications. Moreover, the hybrid machine is prepared to handle multiple spray materials, opening new avenues for creating multimaterial components. The ability to customize parts with distinct material properties, ranging from structural to bioactive functionalities, paves the way for advances in personalized implants and multifunctional industrial components. Experimental validation of the system was performed on both curved surfaces and substrates distinct from the deposited materials, using materials like titanium and mild steel. Characterization through SEM and EDS confirms the topology and versatility of customized parts, illustrating the promise of this system for future applications. The research lays the foundation for future developments in hybrid manufacturing, aiming to incorporate real-time defect detection, adaptive control, and AI-driven customization, ultimately enhancing automation and personalization in manufacturing. |
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| Autores principais: | Freitas, Bruno Henrique Matos |
| Assunto: | Additive manufacturing Hybrid manufacturing Multimaterial Robotics Subtractive machining Manufatura aditiva Manufatura híbrida Manufatura subtrativa Robótica Engenharia e Tecnologia::Engenharia Mecânica |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | tese de doutoramento |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | This dissertation explores the development and implementation of a cutting-edge hybrid manufacturing (HM) system that integrates both additive and subtractive processes within a single robotic-assisted setup. This hybrid system addresses the inefficiencies and inaccuracies common in traditional manufacturing workflows, which often require the use of multiple machines and manual part transfers: issues particularly prevalent when producing complex, micro-scale, and biomedical components. By combining laser-based additive manufacturing (AM) with multi-axis CNC subtractive machining (SM), the system allows for the precise customization of intricate geometries and surface characteristics. A key innovation of this research lies in the integration of a unique nonplanar slicer, combined with inverse kinematics of a 7-axis robotic system (5-axis cnc + 2-axis galvo scan head), to effectively manage the complexities of curved surfaces. This innovative approach ensures highly accurate material removal and processing through laser, even on non-planar surfaces, a critical feature when customizing components for biomedical applications. Moreover, the hybrid machine is prepared to handle multiple spray materials, opening new avenues for creating multimaterial components. The ability to customize parts with distinct material properties, ranging from structural to bioactive functionalities, paves the way for advances in personalized implants and multifunctional industrial components. Experimental validation of the system was performed on both curved surfaces and substrates distinct from the deposited materials, using materials like titanium and mild steel. Characterization through SEM and EDS confirms the topology and versatility of customized parts, illustrating the promise of this system for future applications. The research lays the foundation for future developments in hybrid manufacturing, aiming to incorporate real-time defect detection, adaptive control, and AI-driven customization, ultimately enhancing automation and personalization in manufacturing. |
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