Eunseob Kim

Papers

Total Citations

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About

Eunseob Kim is a leading researcher at the intersection of smart manufacturing, predictive maintenance (PdM), and human–machine collaboration. His work focuses on developing intelligent sensing systems that emulate human sensory expertise—particularly hearing and intuition—to monitor industrial machinery. Kim’s most cited paper, “Development of internal sound sensor using stethoscope and its applications for machine monitoring” (2020, 25 citations), introduces a novel approach that adapts the medical stethoscope for internal sound detection in rotary equipment, enabling early fault diagnosis in IoT-enabled smart factories. This work bridges biomedical sensing principles with industrial PdM, offering a low-cost, high-sensitivity alternative to traditional vibration monitoring. In his 2021 paper “Human Expertise Inspired Smart Sensing and Manufacturing” (5 citations), Kim advances the concept of cognitive manufacturing by integrating human auditory intuition into autonomous sensing frameworks. His contributions are pivotal for realizing Industry 4.0’s vision of adaptive, human-centric automation. By fusing domain expertise with sensor innovation, Kim is shaping a future where machines listen—and learn—like skilled technicians.