Silas Z. Gebrehiwot
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1
Total Citations
1
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1
About
Silas Z. Gebrehiwot is a researcher at the intersection of additive manufacturing and computer vision, whose work focuses on advancing the quality assurance of 3D-printed components. His primary research areas include automated defect detection, mechanical testing of polymer-based printed parts, and the integration of machine learning with manufacturing processes. Gebrehiwot’s most notable contribution is his 2024 paper, "Automated Quality Control of 3D Printed Tensile Specimen via Computer Vision," which introduces a novel, non-destructive method for identifying structural flaws in printed tensile specimens using real-time image analysis. This work addresses a critical bottleneck in additive manufacturing—ensuring part reliability without costly manual inspection—and has the potential to streamline production in industries from aerospace to biomedical devices. While his citation count is still emerging, the paper’s practical implications have already drawn interest from labs exploring scalable quality control systems. Gebrehiwot’s approach combines rigorous experimental design with accessible computer vision techniques, making his research a valuable resource for students and engineers seeking to bridge the gap between 3D printing and automated inspection.
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Top Papers
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