Article
Green & Sustainable Science & Technology
Bin He, Xiaoyang Cao, Yicheng Hua
Summary: This paper analyzes the role of digital twin technology in achieving sustainable development goals, focusing on theoretical research on the detection process of massage chairs by intelligent detection robots, information fusion, and DS evidence theory. By establishing a quantitative model, determining weights using the entropy weight method, and evaluating the sustainability of products through data fusion, the comprehensive performance in sustainable design is improved.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Engineering, Industrial
Yang Xie, Kunlei Lian, Qiong Liu, Chaoyong Zhang, Hongqi Liu
Summary: Recent developments in internet technology, IoT, cloud computing, big data, and AI have significantly advanced manufacturing, with digitalization playing a key role in increasing productivity. The use of digital twin-driven tools and service modes offers modern solutions to meet customer demands, while virtual cutting tool test platforms provide guidance for future intelligent manufacturing. Prospects and challenges in data analysis, fusion, mining, and services are also discussed for further development in the field.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Engineering, Industrial
Zexuan Zhu, Xiaolin Xi, Xun Xu, Yonglin Cai
Summary: This paper introduces a Digital Twin-driven thin-walled part manufacturing framework, which utilizes Digital Twin technology to improve the efficiency of thin-walled parts machining and manage trial machining processes in real-time through interactive digital data.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Chemistry, Multidisciplinary
Eunyoung Heo, Namhyun Yoo
Summary: In NC-based machining, NC data-based tool paths affect quality and productivity. It is difficult to perfectly predict cutting dynamics, which may lead to errors in tool-path optimization. This study attempts to synchronize spindle load and NC data to uniformize machining load using digital-twin technology, resulting in improved chatter reduction and processing time optimization.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Marine
Qingcai Wu, Yunsheng Mao, Jianxun Chen, Chong Wang
Summary: Digital twin has attracted extensive attention for its potential in future interactions with physical and virtual worlds. This paper reviews the applications of digital twins in intelligent manufacturing, focusing on a digital twin-driven ship intelligent manufacturing system. Five main parts of the application framework are discussed, along with key enabling techniques and a case study in pipe machining production line to validate the proposed approach.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2021)
Article
Engineering, Civil
Xiaolong Xu, Zhongjian Liu, Muhammad Bila, S. Vimal, Houbing Song
Summary: Mobile edge computing (MEC) reduces transmission latency in intelligent transportation systems (ITS) by offloading computation tasks to RSUs and utilizing decision theory for optimal strategies. The use of digital twin (DT) enhances decision-making by constructing a virtual world reflecting the physical world. Simulation results demonstrate the superiority of the proposed method over other baselines.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Chao Sun, Javier Dominguez-Caballero, Rob Ward, Sabino Ayvar-Soberanis, David Curtis
Summary: Accurate prediction of machining cycle times is crucial in the manufacturing industry. Existing methods often underestimate the cycle times. This study proposes a data-driven approach using neural network models, achieving over 90% accuracy in estimating machining times.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Computer Science, Artificial Intelligence
B. D. Deebak, Fadi Al-Turjman
Summary: The rapid development of information technologies has led to the transition towards intelligent manufacturing, with the application of digital-twin technology playing a key role. Industrial manufacturers are aiming to transform equipment into fully automated systems to meet future market demands. This article proposes a digital-twin-assisted fault diagnosis using deep transfer learning, showcasing the accuracy of an intelligent tool-holder in optimizing cutting tool operations.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Wenkai Zhao, Rongyi Li, Xianli Liu, Jun Ni, Chao Wang, Canlun Li, Libo Zhao
Summary: A digital twin system for controlling processing errors in thin-walled parts was built using a microservices architecture. A method for building a digital twin system at the processing unit level with the best coupling degree was proposed, mainly targeting the dynamic characteristics analysis knowledge base of thin-walled parts. Furthermore, a comprehensive solution including the construction, operation, evaluation, optimization, and visualization of a knowledge base for the dynamic characteristics of the processing unit was proposed to meet the requirements for backward compatibility of the digital twin system at the processing unit level, providing guidance for the digital transformation and upgrading of CNC machine tools and the optimization of processing technology based on digital twin technology.
Article
Computer Science, Artificial Intelligence
Jinfeng Liu, Xiaojian Wen, Honggen Zhou, Sushan Sheng, Peng Zhao, Xiaojun Liu, Chao Kang, Yu Chen
Summary: This paper presents a multidimensional modeling approach for machining processes using Digital Twin technology, which supports the design and execution phases of intelligent machining. The effectiveness of the applied framework and the proposed method is verified through testing key components of diesel engines.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Engineering, Mechanical
Xin Fang, Guijie Liu, Honghui Wang, Xiaojie Tian
Summary: This paper proposes a digital twin method based on multi-source data fusion for crack growth prediction. By constructing two different prediction methods and incorporating consistency retention method and crack detection data, dynamic prediction of crack growth is achieved.
ENGINEERING FAILURE ANALYSIS
(2023)
Article
Engineering, Industrial
Zhifeng Liu, Wei Chen, Caixia Zhang, Congbin Yang, Qiang Cheng
Summary: This study integrates the advantages of a digital twin and supernetwork to develop an intelligent scheduling method for workshops, enabling rapid and efficient generation of process plans and intelligent workshop scheduling. The proposed method has been verified for its efficiency through a case study of an aeroengine gear production workshop.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Engineering, Manufacturing
Xian Cao, Gang Zhao, Wenlei Xiao
Summary: Digital Twin has become a frontier research topic and an important development direction in intelligent manufacturing. This article analyzes and explains the challenges faced by machining simulation and proposes a new machining simulation system to meet these challenges. The system utilizes the STEP-NC standard to save complete process data, develops a synchronization algorithm based on the communication data of the computer numerical control system, and introduces an optimized tri-dexel-based machining simulation algorithm for high efficiency. A Digital Twin system for NC machining is presented and tested in a workshop.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE
(2022)
Article
Computer Science, Information Systems
Haya Elayan, Moayad Aloqaily, Mohsen Guizani
Summary: The field of digital smart healthcare has rapidly advanced, with digital twin technology expected to revolutionize the concept of digital healthcare and improve operational efficiency. The implementation of an intelligent healthcare system using the digital twin framework successfully created a classifier model for ECG heart rhythms to diagnose heart disease and detect heart problems.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Automation & Control Systems
Charles Ming Zheng, Lu Zhang, Yaw-Hong Kang, Youji Zhan, Yongchao Xu
Summary: This paper proposes a digital twin-driven intelligent algorithm for monitoring in-process milling parameters. The algorithm extracts milling parameters using force sensor and achieves a balance between identification accuracy and calculation efficiency. The proposed algorithm is validated through milling experiments.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)