Qingwei Nie

According to our database, Qingwei Nie authored at least 9 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

An augmented reality-assisted interaction approach using deep reinforcement learning and cloud-edge orchestration for user-friendly robot teaching.

Changchun Liu, Dunbing Tang, Haihua Zhu, Qingwei Nie, Wei Chen, Zhen Zhao

Robotics Comput. Integr. Manuf., February, 2024

2023

A mixed perception-based human-robot collaborative maintenance approach driven by augmented reality and online deep reinforcement learning.

Changchun Liu, Zequn Zhang, Dunbing Tang, Qingwei Nie, Linqi Zhang, Jiaye Song

Robotics Comput. Integr. Manuf., October, 2023

A multi-agent and cloud-edge orchestration framework of digital twin for distributed production control.

Qingwei Nie, Dunbing Tang, Changchun Liu, Liping Wang, Jiaye Song

Robotics Comput. Integr. Manuf., August, 2023

A transfer learning CNN-LSTM network-based production progress prediction approach in IIoT-enabled manufacturing.

Changchun Liu, Haihua Zhu, Dunbing Tang, Qingwei Nie, Shipei Li, Yi Zhang, Xuan Liu

Int. J. Prod. Res., 2023

2022

An Augmented Reality-Assisted Prognostics and Health Management System Based on Deep Learning for IoT-Enabled Manufacturing.

Liping Wang, Dunbing Tang, Changchun Liu, Qingwei Nie, Zhen Wang, Linqi Zhang

Sensors, 2022

Probing an intelligent predictive maintenance approach with deep learning and augmented reality for machine tools in IoT-enabled manufacturing.

Changchun Liu, Haihua Zhu, Dunbing Tang, Qingwei Nie, Tong Zhou, Liping Wang, Yejia Song

Robotics Comput. Integr. Manuf., 2022

A multi-agent and internet of things framework of digital twin for optimized manufacturing control.

Qingwei Nie, Dunbing Tang, Haihua Zhu, Hongwei Sun

Int. J. Comput. Integr. Manuf., 2022

2021

Research on Workers Integration in Smart Factories With Multi-Agent Control System.

Zequn Zhang, Dunbing Tang, Qingwei Nie

IEEE Access, 2021

A Novel Predictive Maintenance Method Based on Deep Adversarial Learning in the Intelligent Manufacturing System.

Changchun Liu, Dunbing Tang, Haihua Zhu, Qingwei Nie

IEEE Access, 2021