On June 19, 2025, the Global Research Laboratory(GRL) team organized a special session at the 2024 Spring Conference of the Korean Reliability Society. This session showcased recent advancements in reliability engineering and intelligent systems, with four presentations delivered by GRL-affiliated researchers and collaborators.
The session opened with "Memory Bank Guided Diffusion Model for Lightweight Anomaly Detection" by Woojoon Lee and Pilsung Kang (Seoul National University), proposing a memory-augmented diffusion model for efficient anomaly detection.
Next, Yosep Na and Jaewook Song (Hanyang University) presented "Probabilistic Forecasting of Lithium-Ion Battery Health Indicators Using Autoregressive Recurrent Neural Networks," which offered a data-driven approach for forecasting battery degradation trends.
Jaeyoung Lee, Euijin Kim, Hyunah Jeon, and Misuk Kim (Hanyang University) introduced their work titled "Multimodal Data Generation and Validation for Bearing Fault Diagnosis using LLMs," leveraging large language models to enhance the diversity and validity of condition monitoring datasets.
Finally, Hwi Jun Jung and Suk-Joo Bae (Hanyang University) presented "Process Monitoring via Zero-Inflated Multivariate Generalized Pareto Distributions for Serial Multi-Stage Process Data," suggesting a novel statistical modeling framework for reliability monitoring in complex systems.
The session provided a valuable opportunity to share ongoing research and strengthen academic exchange in the field of reliability.
On June 19, 2025, the Global Research Laboratory(GRL) team organized a special session at the 2024 Spring Conference of the Korean Reliability Society. This session showcased recent advancements in reliability engineering and intelligent systems, with four presentations delivered by GRL-affiliated researchers and collaborators.
The session opened with "Memory Bank Guided Diffusion Model for Lightweight Anomaly Detection" by Woojoon Lee and Pilsung Kang (Seoul National University), proposing a memory-augmented diffusion model for efficient anomaly detection.
Next, Yosep Na and Jaewook Song (Hanyang University) presented "Probabilistic Forecasting of Lithium-Ion Battery Health Indicators Using Autoregressive Recurrent Neural Networks," which offered a data-driven approach for forecasting battery degradation trends.
Jaeyoung Lee, Euijin Kim, Hyunah Jeon, and Misuk Kim (Hanyang University) introduced their work titled "Multimodal Data Generation and Validation for Bearing Fault Diagnosis using LLMs," leveraging large language models to enhance the diversity and validity of condition monitoring datasets.
Finally, Hwi Jun Jung and Suk-Joo Bae (Hanyang University) presented "Process Monitoring via Zero-Inflated Multivariate Generalized Pareto Distributions for Serial Multi-Stage Process Data," suggesting a novel statistical modeling framework for reliability monitoring in complex systems.
The session provided a valuable opportunity to share ongoing research and strengthen academic exchange in the field of reliability.