Sang Min Yang

Bayesian-based uncertainty-aware tool-wear prediction model in end-milling process of titanium alloy

Gyeongho Kim, Sang Min Yang, Dong Min Kim et al. · Applied Soft Computing · 2023 · 45 citations · Full text

Convolutional Neural Network, Engineering, Machine Learning +13

A multi-domain mixture density network for tool wear prediction under multiple machining conditions

Gyeongho Kim, Sang Min Yang, Sinwon Kim et al. · International Journal of Production Research · 2023 · 27 citations · Full text

Developing a data-driven system for grinding process parameter optimization using machine learning and metaheuristic algorithms

Gyeongho Kim, S W Park, Jae Gyeong Choi et al. · CIRP journal of manufacturing science and technology · 2024 · 25 citations

Data-driven Optimization, Engineering, Machine Learning +11

Developing a deep learning-based uncertainty-aware tool wear prediction method using smartphone sensors for the turning process of Ti-6Al-4V

Gyeongho Kim, Sang Min Yang, Dong Min Kim et al. · Journal of Manufacturing Systems · 2024 · 24 citations

Wearable System, Mobile Sensing, Engineering +6

Fisher-informed continual learning for remaining useful life prediction of machining tools under varying operating conditions

Gyeongho Kim, Yun Seok Kang, Sang Min Yang et al. · Reliability Engineering & System Safety · 2024 · 23 citations

Engineering, Machine Learning, Industrial Engineering +14