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S

Sang Min Yang

department of mechanical engineering

H指数:7

被引数:224

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Intelligent digital twin process for the end-milling simulation combined with a multi-physical model

基于多物理模型结合的端铣仿真智能数字孪生工艺

Journal of Intelligent Manufacturing

IF7.4

2025-09-300

PRE

Artificial intelligence augmented digital twin for improving the machinability in a robotic carbon fiber reinforced plastics machining process

人工智能增强的数字孪体，用于改进机器人碳纤维增强塑料加工过程的可加工性

Journal of Intelligent Manufacturing

IF7.4

2025-06-170

PRE

Investigation of wear behavior for large pulsed electron beam irradiated cutting tools under the turning process of Ti-6Al-4V

JOURNAL OF MANUFACTURING PROCESSES

IF6.8

2025-04-010

PRE

Experimental investigation of tool wear and surface integrity using a large pulsed electron beam (LPEB) irradiated end-mill cutting tool for Ti-6Al-4 V

JOURNAL OF MANUFACTURING PROCESSES

IF6.8

2025-04-010

PRE

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

RELIABILITY ENGINEERING & SYSTEM SAFETY

IF11

2025-01-010

PRE

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

JOURNAL OF MANUFACTURING SYSTEMS

IF14.2

2024-10-013

PRE

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

INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH

IF7.3

2023-12-0611

OA

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

APPLIED SOFT COMPUTING

IF6.6

2023-11-0118

OAAI

Improvement of tool life via unique surface modification of a tungsten carbide tool using a large pulsed electron beam in Ti-6Al-4V machining

通过在Ti-6Al-4V加工中使用大脉冲电子束对碳化钨刀具进行独特的表面改性来提高刀具寿命

JOURNAL OF MANUFACTURING PROCESSES

IF6.8

2022-11-017

PRE