Papers
1
Total Citations
9
H-Index
1
About
Minsub Kim is a researcher specializing in predictive maintenance, system degradation assessment, and accelerated degradation testing, with a focus on electromechanical systems. His work centers on developing model-based approaches to forecast the remaining useful life of critical components, particularly servo motors, which are essential in industrial automation and robotics. In his most-cited study, "Experimental study on the life prediction of servo motors through model-based system degradation assessment and accelerated degradation testing" (2018), Kim proposed a novel framework that integrates degradation modeling with accelerated testing to improve the accuracy and efficiency of life predictions. This contribution addresses a key challenge in reliability engineering: balancing test time with realistic failure data. Although his citation count is still growing, his work has been recognized for its practical implications in reducing downtime and maintenance costs in manufacturing. Kim’s research bridges theoretical modeling and experimental validation, offering a systematic methodology that can be extended to other rotating machinery. His efforts contribute to the broader field of prognostics and health management (PHM), making him a promising voice in the push toward smarter, data-driven industrial maintenance.
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Top Papers
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