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The rapid advancement of advanced manufacturing techniques has opened new opportunities for developing personalized medical devices tailored to individual patient needs. Unlike conventional mass-produced solutions, personalized devices are designed using patient-specific anatomical and physiological data, ensuring higher comfort, enhanced performance, and improved treatment outcomes. This paper presents an integrated approach that combines advanced imaging modalities, computer-aided design (CAD), and cutting-edge manufacturing methods such as additive manufacturing, selective laser melting, and precision CNC machining to create customized medical devices. The process begins with acquiring accurate patient data through medical imaging techniques such as CT or MRI scans, which are then processed to develop three-dimensional models. These models undergo optimization based on mechanical, biocompatibility, and ergonomic considerations before fabrication. Algorithms for geometry adaptation, topology optimization, and material distribution are incorporated to enhance device functionality and durability. Additionally, mathematical modeling is employed to predict stress distribution and performance under physiological loading conditions. The proposed methodology is validated through case studies involving orthopedic implants, dental prosthetics, and wearable assistive devices. Experimental results demonstrate that the developed devices meet stringent medical standards while significantly reducing production lead time compared to traditional methods. The findings indicate that advanced manufacturing, coupled with data-driven design, offers a robust pathway toward scalable and cost-effective personalized healthcare solutions.
"Development of Personalized Medical Devices using Advanced Manufacturing Techniques", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.6, Issue 7, page no.125-130, July-2021, Available :http://www.ijrti.org/papers/IJRTI2107022.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator