Research Goals

Sensing: Develop advanced sensor technologies and data acquisition systems to efficiently collect, preprocess, and integrate high-dimensional data from manufacturing and mechanical systems, enabling accurate real-time monitoring.

Modeling: Create surrogate models that leverage sensor data to approximate complex mechanical phenomena, integrating physical knowledge and data-driven techniques for more interpretable and reliable predictions.

Optimization: Improve model generalization for practical applications such as process optimization, control parameter tuning, and product quality enhancement through data-driven techniques and real-time model adaptation.

Reliability: Develop monitoring, fault diagnosis, and Prognostics and Health Management (PHM) algorithms to ensure operational reliability, optimize maintenance schedules, and predict system failures before they occur, ensuring long-term system health and robustness.

Research Area

• 설비/공정/품질 분야 스마트 제조를 위한 빅데이터 기반 최적화/모델링

• 검사, 계측 센서 신뢰성 확보를 위한 실험/최적화/모델링

• 머신 인텔리전스를 위한 엣지 애널리틱스

• 산업 인공지능(Industrial Artificial Intelligence) 애플리케이션 개발