A survey of immersive technologies and applications for industrial product development

R Liu, C Peng, Y Zhang, H Husarek, Q Yu - Computers & Graphics, 2021 - Elsevier
With the expanded digitalization of manufacturing and product development process,
research into the use of immersive technology in smart manufacturing has increased. The …

[HTML][HTML] AI-assisted monitoring of human-centered assembly: A comprehensive review

V Selvaraj, S Min - International Journal of Precision Engineering and …, 2023 - ijpem-st.org
Detection and localization of activities in a human-centric manufacturing assembly operation
will help improve manufacturing process optimization. Through the human-in-loop …

Acceleration-based activity recognition of repetitive works with lightweight ordered-work segmentation network

N Yoshimura, T Maekawa, T Hara, A Wada… - Proceedings of the …, 2022 - dl.acm.org
This study presents a new neural network model for recognizing manual works using body-
worn accelerometers in industrial settings, named Lightweight Ordered-work Segmentation …

Multi-sensor fusion based industrial action recognition method under the environment of intelligent manufacturing

Z Wang, J Yan - Journal of Manufacturing Systems, 2024 - Elsevier
In the context of intelligent manufacturing and Industry 4.0, the manufacturing industry is
rapidly transitioning toward mass personalization production. Despite this trend, the …

Toward practical factory activity recognition: unsupervised understanding of repetitive assembly work in a factory

T Maekawa, D Nakai, K Ohara, Y Namioka - Proceedings of the 2016 …, 2016 - dl.acm.org
In a line production system of a factory, a worker repetitively performs predefined operation
processes. This paper tries to recognize work by factory workers in an unsupervised …

Robust unsupervised factory activity recognition with body-worn accelerometer using temporal structure of multiple sensor data motifs

Q **a, J Korpela, Y Namioka, T Maekawa - Proceedings of the ACM on …, 2020 - dl.acm.org
This paper presents a robust unsupervised method for recognizing factory work using
sensor data from body-worn acceleration sensors. In line-production systems, each factory …

Action recognition in manufacturing assembly using multimodal sensor fusion

M Al-Amin, W Tao, D Doell, R Lingard, Z Yin… - Procedia …, 2019 - Elsevier
Production innovations are occurring faster than ever. Manufacturing workers thus need to
frequently learn new methods and skills. In fast changing, largely uncertain production …

Robust activity recognition for aging society

Y Chen, L Yu, K Ota, M Dong - IEEE journal of biomedical and …, 2018 - ieeexplore.ieee.org
Human activity recognition (HAR) is widely applied to many industrial applications. In the
context of Industry 4.0, driven by the same demand of machines' self-organizing ability, HAR …

Worker Activity Recognition in Manufacturing Line Using Near-body Electric Field

S Suh, VF Rey, S Bian, YC Huang… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Manufacturing industries strive to improve production efficiency and product quality by
deploying advanced sensing and control systems. Wearable sensors are emerging as a …

Unsupervised factory activity recognition with wearable sensors using process instruction information

X Qingxin, A Wada, J Korpela, T Maekawa… - Proceedings of the …, 2019 - dl.acm.org
This paper presents an unsupervised method for recognizing assembly work done by factory
workers by using wearable sensor data. Such assembly work is a common part of line …