Kyoung-Seo Ki

Papers

Total Citations

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About

Kyoung-Seo Ki is a researcher whose work lies at the intersection of manufacturing process optimization and applied statistical modeling, with a particular focus on improving the quality and efficiency of automated welding systems. His most cited paper, "Global and Cluster-wise Regression Models for Total Bead Area as Welding Quality" (2019), which has garnered 4 citations, introduces a novel algorithmic approach to estimating optimal welding parameters. Ki’s major contribution is the development of a dual-model framework that combines global and cluster-wise regression techniques to predict total bead area—a critical indicator of weld quality. This work addresses a key challenge in high-volume production industries, where automated welding must balance precision with adaptability for varying part geometries. By enabling more accurate parameter estimation, Ki’s research helps reduce defects and improve consistency in manufacturing processes. His findings are particularly valuable for engineers and researchers working on smart manufacturing and Industry 4.0 applications, where data-driven optimization is essential. Though early in his career, Ki’s focused contributions to welding quality modeling demonstrate a promising trajectory in applied industrial research.