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, Industrial
Qizhang Zhu, Sihan Huang, Guoxin Wang, Shokraneh K. Moghaddam, Yuqian Lu, Yan Yan
Summary: This paper proposes a dynamic reconfiguration optimization method for intelligent manufacturing systems with human-robot collaboration based on digital twin, considering the different characteristics between operators and robots. By constructing a multi-objective optimization model and adopting the nondominated sorting genetic algorithm-II, efficient tasks allocation is achieved to improve production efficiency.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Jiwei Zhang, Haoliang Cui, Andy L. Yang, Feng Gu, Chengjie Shi, Wen Zhang, Shaozhang Niu
Summary: This paper proposes an Intelligent Digital Twin System (IDTS) based on artificial intelligence and digital twins for the paper industry. The system includes prediction models for various industry processes such as stirring speed, water consumption, air pressure, and exhaust air temperature. By collecting data and analyzing important indicators, the IDTS improves energy utilization and production efficiency, resulting in cost savings. Its effectiveness has been demonstrated in an actual paper manufacturing factory by improving operational efficiency and saving labor and maintenance costs.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Automation & Control Systems
Hongfei Guo, Yingxin Zhu, Yu Zhang, Yaping Ren, Minshi Chen, Rui Zhang
Summary: This paper proposes a discrete manufacturing workshop layout optimization method based on digital twin, which solves layout problems through data fusion, information interaction, and data analysis, resulting in a 29.4% increase in production capacity when applied to a welding production workshop.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Chemistry, Multidisciplinary
Jinghua Li, Wenhao Yin, Boxin Yang, Li Chen, Ruipu Dong, Yidong Chen, Hanchen Yang
Summary: In this paper, a comprehensive system architecture based on digital twin technology is proposed to improve the production efficiency and competitiveness of ocean engineering manufacturing industry. By establishing a planning model based on graph neural networks and suggesting five decision-support approaches, the problems in production planning and scheduling can be effectively addressed, achieving the goals of rapid processing and just-in-time completion. The research findings demonstrate that the proposed method outperforms traditional scheduling rules and heuristics in terms of precision rate and rapidity, and the digital twin system supports its full-scale application in future smart factories.
APPLIED SCIENCES-BASEL
(2023)
Review
Engineering, Manufacturing
Bin He, Kai-Jian Bai
Summary: Intelligent manufacturing as the next-generation system improves productivity, reduces costs, and enhances flexibility. Sustainable manufacturing is gaining attention, with digital twin technology playing a crucial role in real-time monitoring and predictive maintenance of intelligent manufacturing systems.
ADVANCES IN MANUFACTURING
(2021)
Article
Computer Science, Interdisciplinary Applications
Weiwei Qian, Yu Guo, Hao Zhang, Shaohua Huang, Litong Zhang, Hailang Zhou, Weiguang Fang, Shanshan Zha
Summary: This article focuses on how to effectively construct DTM synchronous update methods based on dynamic sample data for discrete manufacturing workshop, in order to enhance the accuracy of PP prediction. The proposed model demonstrates good performance in realizing the synchronization of workshop performance in industrial environment, greatly improving the prediction ability for PP.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Computer Science, Artificial Intelligence
Quanyong Zhang, Shengnan Shen, Hui Li, Wan Cao, Wen Tang, Jing Jiang, Mingxing Deng, Yunfan Zhang, Beikang Gu, Kangkang Wu, Kun Zhang, Sheng Liu
Summary: In the electronics manufacturing industry, digital twin technology plays a significant role in driving intelligent and digital production lines. This study successfully developed an intelligent production line for automotive MEMS pressure sensors driven by digital twin, achieving 24/7 unattended operation with a product yield above 98% and a takt time of less than 16 seconds.
ADVANCED ENGINEERING INFORMATICS
(2022)
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
Chemistry, Analytical
Arif Furkan Mendi
Summary: Digital twin technology has significant advantages in the manufacturing sector, particularly in product development and the commercial production phase of production lines. It allows for simulation, processing, and validation of each stage of the product, leading to the discovery of potential problems and increased production efficiency.
Article
Engineering, Industrial
Tianxiang Kong, Tianliang Hu, Tingting Zhou, Yingxin Ye
Summary: This paper proposes a data construction method to provide stable and efficient data support for the applications of Digital Twin System (DTS). The framework is designed based on functional requirements and includes modules for data representation, organization, and management. A case study on cutting tool wear prediction demonstrates the feasibility and effectiveness of the proposed method.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Yueze Zhang, Caixia Zhang, Jun Yan, Congbin Yang, Zhifeng Liu
Summary: This paper proposes a rapid construction method of equipment model (RCMEM) for a discrete manufacturing digital twin workshop system, which can meet the requirements of complex manufacturing business scenarios and improve the efficiency and quality of equipment-level digital twin model construction.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Automation & Control Systems
Daqiang Guo, Ray Y. Zhong, Yiming Rong, George G. Q. Huang
Summary: This article introduces the concepts and principles of shop-floor logistics and manufacturing synchronization. It proposes an overall framework based on an intelligent manufacturing system and explores synchronization mechanisms using mixed-integer programming and an equivalent constraint programming model. The case study demonstrates the advantages of this approach.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Zhongtai Hu, Xifeng Fang, Jie Zhang
Summary: The research and application of digital twin technology provide new technical means for the development of various fields. A digital twin workshop for marine diesel engine manufacturing was constructed, offering new ideas for technological innovation in the manufacturing industry.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Engineering, Industrial
Weiwei Qian, Yu Guo, Litong Zhang, Shengbo Wang, Shaohua Huang, Sai Geng
Summary: This article focuses on the systematic and effective construction of digital twin model methods for discrete manufacturing workshops (DMW). Three key technologies related to digital twin in DMW are proposed, including model migration based matching modeling technology, graph convolutional network and temporal convolutional network based DT model verification, and Adaboost based synchronous evolution of DT model. The experiment demonstrates the good performance and holistic understanding of the proposed methods for physical workshop in industrial environment.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)