Review
Engineering, Industrial
Jiewu Leng, Yuanwei Zhong, Zisheng Lin, Kailin Xu, Dimitris Mourtzis, Xueliang Zhou, Pai Zheng, Qiang Liu, J. Leon Zhao, Weiming Shen
Summary: Manufacturers are realizing the importance of system resilience and considering the use of Decentralized Autonomous Organization (DAO) to achieve decentralized autonomous manufacturing and resilient Industry 5.0 vision. This paper reviews the literature on Decentralized Manufacturing (DM) and Autonomous Manufacturing (AM), and proposes a manufacturing paradigm called Decentralized Autonomous Manufacturing (DAM). Future research directions and challenges of DAM are highlighted.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Engineering, Industrial
Jiewu Leng, Weinan Sha, Zisheng Lin, Jianbo Jing, Qiang Liu, Xin Chen
Summary: This paper proposes a blockchained smart contract pyramid-driven multi-agent autonomous process control approach to improve the timeliness and adaptability of control in resilient individualized manufacturing. The approach includes a blockchain-based multi-agent system architecture, a quad-play blockchained smart contract pyramid, and decentralized control patterns. A prototype of the system is built and experiments are conducted in different environments.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Haoqi Wang, Lindong Lv, Xupeng Li, Hao Li, Jiewu Leng, Yuyan Zhang, Vincent Thomson, Gen Liu, Xiaoyu Wen, Chunya Sun, Guofu Luo
Summary: Safety management is crucial for human-centered manufacturing in Industry 5.0, but there are three challenges to bridge the gap between current workshop safety management and the desired requirements. To address these challenges, a reasoning approach using Digital Twin is proposed, which includes a machine-readable semantic reasoning framework, modeling of unsafe states ontology, and the construction of a high-fidelity virtual Digital Twin Workshop. The approach is validated through an experiment and shows promising results.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Cristina Alcaraz, Javier Lopez
Summary: This article proposes a layered protection framework for 6G-enabled IIoT environments, aiming to fully protect DTs, DTNs, and the entire 6G ecosystem to achieve the goals of Industry 5.0.
Article
Chemistry, Analytical
Gianfranco E. Modoni, Marco Sacco
Summary: This work presents a digital-twin-based framework that focuses on integrating human-centered processes into Industry 5.0. By including workers and their digital replicas in the loop of the digital twin, the proposed framework extends the traditional model by considering the human component. The goal is to provide a reference architecture for manufacturing companies for a digital-twin-based platform that combines humans and machines through monitoring, simulation, and optimization of their interactions.
Article
Computer Science, Interdisciplinary Applications
Yongli Wei, Tianliang Hu, Lili Dong, Songhua Ma
Summary: The traditional product development process is inefficient due to the optimization and redesign work between the design stage and the prototype design and manufacturing stage. The manufacturing phase for physical prototypes is time-consuming and costly. To address these issues, a digital twin-driven manufacturing equipment development method is proposed, incorporating axiomatic design theory, DT modeling, and DT-based validation analysis. This method eliminates the need for physical prototyping, reduces product development time, and enhances efficiency.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Chemistry, Multidisciplinary
Kyu Tae Park, Yoo Ho Son, Sang Wook Ko, Sang Do Noh
Summary: To achieve efficient personalized production at an affordable cost, modular manufacturing systems (MMS) can be used, with a micro smart factory (MSF) being an example of MMS with heterogeneous production processes. However, MSFs need to overcome performance hurdles with respect to production control, which is why a digital twin (DT) and reinforcement learning (RL)-based production control method is proposed in this paper to provide a resilient solution for the cyber-physical production systems (CPPSs) architectural framework and to make appropriate decisions in dynamic production situations.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Industrial
Joze M. Rozanec, Inna Novalija, Patrik Zajec, Klemen Kenda, Hooman Tavakoli Ghinani, Sungho Suh, Entso Veliou, Dimitrios Papamartzivanos, Thanassis Giannetsos, Sofia Anna Menesidou, Ruben Alonso, Nino Cauli, Antonello Meloni, Diego Reforgiato Recupero, Dimosthenis Kyriazis, Georgios Sofianidis, Spyros Theodoropoulos, Blaz Fortuna, Dunja MladeniC, John Soldatos
Summary: Human-centricity is the core value in the evolution of manufacturing towards Industry 5.0. However, there is a lack of architecture considering safety, trustworthiness, and human-centricity. Therefore, a proposed architecture integrating Artificial Intelligence, simulated reality, decision-making, and users' feedback, focusing on synergies between humans and machines, is aligned with the Big Data Value Association Reference Architecture Model and validated on three real-world case studies.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Wenjie Jia, Wei Wang, Zhenzu Zhang
Summary: In this paper, a digital twin shop floor is constructed based on the modeling method of complex digital twin. The shop floor covers multi-dimensional information and multi-scale application scenarios, and is divided into simple digital twins focusing on different scales. The implementation of the complex digital twin shop floor demonstrates the feasibility of the proposed modeling method.
ADVANCED ENGINEERING INFORMATICS
(2023)
Review
Computer Science, Artificial Intelligence
Chao Zhang, Zenghui Wang, Guanghui Zhou, Fengtian Chang, Dongxu Ma, Yanzhen Jing, Wei Cheng, Kai Ding, Dan Zhao
Summary: Industry 5.0 complements Industry 4.0 by emphasizing research and innovation as drivers towards a sustainable and human-centric industry. Human-centric smart manufacturing (HSM) utilizes human flexibility, machine precision, and new-generation information technologies to construct a super smart and resilient manufacturing system. This paper conducts a systematic literature review to identify promising research topics and highlights the key enablers, applications, and challenges of HSM.
ADVANCED ENGINEERING INFORMATICS
(2023)
Review
Computer Science, Information Systems
Hassan Alimam, Giovanni Mazzuto, Nicola Tozzi, Filippo Emanuele Ciarapica, Maurizio Bevilacqua
Summary: This paper provides a comprehensive analysis of recent trends in digital twins and traces their evolution to the digital triplet framework. The research aims to enhance the symbiotic relationship between humans and machines, and improve cognitive capabilities and knowledge transfer.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2023)
Article
Engineering, Industrial
Jiewu Leng, Weinan Sha, Baicun Wang, Pai Zheng, Cunbo Zhuang, Qiang Liu, Thorsten Wuest, Dimitris Mourtzis, Lihui Wang
Summary: Industry 5.0 aims to prioritize human well-being in manufacturing systems, achieving social goals beyond employment and growth for the sustainable development of humanity. However, research on Industry 5.0 is still in its early stages and lacks systematic exploration. This paper reviews the evolution and characteristics of Industry 5.0, discusses its connotation system and diversified essence, and proposes a tri-dimensional system architecture for its implementation. It also examines key enablers, future implementation paths, potential applications, and challenges. The limitations of current research are discussed, and potential future research directions are highlighted.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Engineering, Chemical
Kan Wang, Qianqian Hu, Jialin Liu
Summary: The digital twin approach combined with practical experiment has been proposed for the DT-driven process management in the ship industry. By integrating the Bayesian neural network method and DT-based models, this study addresses the fusion issue of multi-source heterogeneous data in the ship operation process and achieves acceptable performances.
Article
Computer Science, Information Systems
Khaled Ali Abuhasel
Summary: Industry 5.0 is a new era characterized by the integration of artificial intelligence and the Internet of Things to achieve sustainable and error-free production operations. This manuscript introduces a Zero-Trust Network-based Access Control Scheme that leverages deep learning to enhance access control and security features.
Article
Computer Science, Information Systems
Yiwen Wu, Ke Zhang, Yan Zhang
Summary: Digital twin network (DTN) utilizes digital twin (DT) technology to create virtual twins of physical objects, enabling co-evolution between physical and virtual spaces. Key applications include manufacturing, aviation, healthcare, and intelligent transportation systems, with current technical challenges and future trends identified.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Artificial Intelligence
Jiewu Leng, Dewen Wang, Xin Ma, Pengjiu Yu, Li Wei, Wenge Chen
Summary: This study proposes a bi-level artificial intelligence model for improving the diagnosis of respiratory diseases using a new generation of information technology. The empirical study demonstrates that the model can provide practical technical support for improving diagnostic accuracy.
APPLIED INTELLIGENCE
(2022)
Article
Computer Science, Interdisciplinary Applications
Hao Zhang, Qiang Liu, Lijun Wei, Jiawei Zeng, Jiewu Leng, Duxi Yan
Summary: This paper presents an iteratively doubling local search approach for the two-dimensional irregular bin packing problem with limited rotations, aiming to pack irregular pieces into the minimum number of rectangular bins iteratively and improving the solution by introducing a waste least first decreasing strategy for piece allocation, utilizing a greedy local search method, and adapting an overlap minimization approach.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Engineering, Industrial
Hao Zhang, Shaowen Yao, Qiang Liu, Lijun Wei, Libin Lin, Jiewu Leng
Summary: This paper studies the constrained two-dimensional guillotine cutting problem with defects and proposes a recursive dynamic programming approach to solve it. The experimental results demonstrate the effectiveness and superiority of the proposed method.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Jiewu Leng, Ziying Chen, Weinan Sha, Shide Ye, Qiang Liu, Xin Chen
Summary: This paper proposes a cloud-edge orchestration-based bi-level autonomous process control framework to improve the production efficiency of rapid PCB prototyping. The framework utilizes blockchained smart contracts and deep learning technology to achieve task coordination and rescheduling decisions. The feasibility and efficiency of the framework are verified through a simulated case based on a rapid PCB prototyping service provider in China.
JOURNAL OF MANUFACTURING SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Jiewu Leng, Ziying Chen, Weinan Sha, Zisheng Lin, Jun Lin, Qiang Liu
Summary: This paper proposes a digital twins-based open architecture production line design and flexible operating approach for individualized manufacturing. The approach enables flexibility in both the physical and software aspects of the production line, and utilizes digital twins for comprehensive characterization and flexible operation. It provides an effective solution for catering to different individualized requirements.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Engineering, Industrial
Jiewu Leng, Weinan Sha, Zisheng Lin, Jianbo Jing, Qiang Liu, Xin Chen
Summary: This paper proposes a blockchained smart contract pyramid-driven multi-agent autonomous process control approach to improve the timeliness and adaptability of control in resilient individualized manufacturing. The approach includes a blockchain-based multi-agent system architecture, a quad-play blockchained smart contract pyramid, and decentralized control patterns. A prototype of the system is built and experiments are conducted in different environments.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Hui Fu, Tuo Zhao, Yanghang Chen, Yipeng Yao, Jiewu Leng
Summary: This paper introduces a new form of smart freeway system that utilizes advanced information and communication technologies to achieve more sustainable objectives. By taking advantage of the digital twin concept, the physical and cyber systems can interact in near-real-time. The paper discusses the framework, operation, and enabled technologies of the digital twin smart freeway (DTSF), and presents a case study to demonstrate the efficiency of the proposed freeway control strategy.
IET INTELLIGENT TRANSPORT SYSTEMS
(2023)
Article
Engineering, Industrial
Haoqi Wang, Lindong Lv, Xupeng Li, Hao Li, Jiewu Leng, Yuyan Zhang, Vincent Thomson, Gen Liu, Xiaoyu Wen, Chunya Sun, Guofu Luo
Summary: Safety management is crucial for human-centered manufacturing in Industry 5.0, but there are three challenges to bridge the gap between current workshop safety management and the desired requirements. To address these challenges, a reasoning approach using Digital Twin is proposed, which includes a machine-readable semantic reasoning framework, modeling of unsafe states ontology, and the construction of a high-fidelity virtual Digital Twin Workshop. The approach is validated through an experiment and shows promising results.
JOURNAL OF MANUFACTURING SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Libin Lin, Lijun Wei, Ting Liu, Hao Zhang, Peihua Qin, Jiewu Leng, Ding Zhang, Qiang Liu
Summary: This article proposes a hierarchical and two-stage framework to address the problem of workstation work overload in mixed-model assembly lines. By using utility workers and considering the workers' health and ergonomic risk, the work overload is effectively managed. The optimization goals are to minimize the number of workstations and utility workers. Furthermore, an iterated greedy algorithm is integrated into a genetics algorithm to achieve global exploration and local exploitation. A divide-and-conquer strategy is also proposed to solve large-scale problems. Experimental results demonstrate the effectiveness of the proposed mechanism in this article.
ENGINEERING OPTIMIZATION
(2023)
Article
Computer Science, Artificial Intelligence
Libin Lin, Ting Liu, Hao Zhang, Jiewu Leng, Lijun Wei, Qiang Liu
Summary: This paper proposes a bilevel improved multi-operator differential evolution algorithm (BL-IMODE) for bilevel optimization, which uses the knowledge transfer and adaptive coordinate systems approach. Experimental results show that BL-IMODE has a significant advantage over other algorithms on three benchmark problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Pan Xiao, Shule Yan, Jinliang Long, Jianfa Lin, Meng Xiao, Nian Cai, Xindu Chen, Jiewu Leng
Summary: An adaptive coarse-to-fine framework is proposed for the automatic first-article inspection of flexographic printing labels (FPLs) based on design drawings. The framework achieves better inspection performance for FPLs than other methods.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Plant Sciences
Hong-Qing Wang, Sheng-Tian Lai, Jian-Bo Liu, Hong-Jie Shao, Ruo-Yun Chen, Jie Kang
Summary: Two new baccharane triterpenes were isolated from Rhus chinensis Mill and their structures were determined using various spectroscopic and analytical techniques.
JOURNAL OF ASIAN NATURAL PRODUCTS RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Jiewu Leng, Zisheng Lin, Zhiqiang Huang, Ruijun Ye, Qiang Liu, Xin Chen
Summary: With the development of simulation technology, more and more manufacturers are using digital twins to design workshops and factories. This paper proposes a rapid simplification approach for 3D geometry models of mechanisms in the context of digital twin-driven manufacturing system design, improving rendering efficiency by reducing computational complexity and preserving shape features.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Engineering, Electrical & Electronic
Rongli Zhao, Zeren Bao, Wanyu Xiao, Shangwen Zou, Guangxin Zou, Yuan Xie, Jiewu Leng
Summary: With the automation of mobile phone assembly, industrial robots are now used in production lines for loading and unloading operations. Currently, industrial robots are primarily used in online teaching mode, which requires pre-set movement and path and repeating point-to-point operation. To address the poor adaptability of loading robots to different products in mobile phone assembly lines, this study proposes a highly adaptive grasping and positioning method for vision-guided right-angle robots.
