Article
Computer Science, Artificial Intelligence
Fuqiang Zhang, Lei Wu, Weichen Liu, Kai Ding, Jizhuang Hui, Jiewu Leng, Xueliang Zhou
Summary: This paper focuses on the stable maintenance of a blockchained shared manufacturing network (BSMN) and proposes an incentive model based on evolutionary game theory to enhance trust and maintain operational stability. The effectiveness of the proposed incentive model is verified through simulation experiments.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Chemistry, Multidisciplinary
Nejc Rozman, Marko Corn, Gasper Skulj, Tomaz Berlec, Janez Diaci, Primoz Podrzaj
Summary: This study investigates the impact of blockchain technology scalability limitations on the performance of Blockchain-Based Shared Manufacturing (BBSM). The findings reveal that a congested blockchain network results in increased transaction costs, reduced service prices, and underutilization of existing maximum production capacities. Allocating funds to financial activities rather than manufacturing activities yields better outcomes for system users. The study highlights the importance of incorporating scalable solutions in blockchain-based manufacturing systems.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Artificial Intelligence
Ming Li, Mingxing Li, Arjun Rachana Harish, George Q. Huang
Summary: This paper proposes a blockchain-based fine-grained digital twin sharing framework to accelerate the popularization and iteration of digital twins in social manufacturing. The framework decomposes complex digital twin instances into small granules and utilizes blockchain for decentralized registering, authorizing, and extracting. The sharing incentive mechanism is also explored to ensure feasibility and sustainability. Experimental results demonstrate the good performance of the sharing mechanism in terms of throughput, latency, and network bandwidth.
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Computer Science, Theory & Methods
Yuxian Li, Jian Weng, Ming Li, Wei Wu, Jiasi Weng, Jia-Nan Liu, Shun Hu
Summary: This paper proposes a novel privacy-preserving sidechain-based scheme called ZeroCross, which aims to address the limitations of existing solutions in terms of privacy concerns. It guarantees transaction unlinkability, exchanging fairness, and value confidentiality through a key exchange mechanism and a verification mechanism. The paper also discusses the impact of remote side-channel attacks in cross-chain exchange and presents a defense strategy. The privacy and security of ZeroCross are proven under the Universal Composability (UC) framework, and the practical performance in terms of computation and communication costs are evaluated.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2022)
Article
Computer Science, Information Systems
Zhe Sun, Peng Zhao, Chunping Wang, Xiaoli Zhang, Hongbing Cheng
Summary: While the number of electric vehicles is increasing rapidly, the supply of public charging piles is insufficient. To address this issue, incorporating idle private charging piles into a shared charging service is crucial. However, existing solutions face challenges in terms of consensus performance and verification for blockchain outputs. In this article, we propose an efficient and secure trading framework built on multiple consortium blockchains, which includes a novel node voting mechanism for improved consensus efficiency and a publicly verifiable design based on the BLS threshold signature technique. The article also introduces a fair and robust trading strategy using smart contracts and presents experimental results demonstrating reduced latency and comparable transaction fees.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Green & Sustainable Science & Technology
Pulin Li, Pingyu Jiang
Summary: Shared factory (SharedF) is a fenceless plant that enables high-efficiency self-organization and sustainability of shared manufacturing resources. The Enhanced Self-organizing Agent (ESA) is proposed as a key technology in this context, facilitating cross-sharing and possessing self-decision making and self-learning abilities.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Engineering, Electrical & Electronic
Yanpeng Li, Huaiyu Wu, Tariku Sinshaw Tamir, Zhen Shen, Sheng Liu, Bin Hu, Gang Xiong
Summary: With improvements in social productivity and technology, consumer demands for personalized and diversified products are increasing, promoting the shift from mass customization to social manufacturing (SM). However, achieving efficient product customization remains a challenge. This paper proposes an efficient product-customization framework using deep learning models and NeRF techniques to generate user-friendly 3D contents for 3D printing, coupled with cloud computing technology for more efficient SM operations. It provides new ideas for collaborative production and insights for the upgrading of manufacturing industries.
Article
Computer Science, Interdisciplinary Applications
Francesco Lupi, Mario G. C. A. Cimino, Tomaz Berlec, Federico A. Galatolo, Marko Corn, Nejc Rozman, Andrea Rossi, Michele Lanzetta
Summary: Today's globalized markets require resilient and agile manufacturing systems with customized and virtualized features. Classical self-standing manufacturing systems are evolving into collaborative networks such as Cloud Manufacturing or Shared Manufacturing as solutions to ensure business continuity. Additive Manufacturing (AM) is a promising technology for innovative production models in Industry 4.0, and this paper proposes a mechanism for sharing workload and resources using AM technology to increase adaptivity. The use of smart contracts and blockchain technology provides decentralized, transparent, and trusted operation in these systems, increasing resilience to disruptive factors.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Yue Wu, Yingfeng Zhang
Summary: With the development of new information technology, smart manufacturing has raised higher requirements for supply chain. Trust evaluation becomes extremely important in the supply chain, which is addressed by the emergence of blockchain technology. This paper proposes an integrated framework and an optimized model to enhance supply chain trust management from different perspectives.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Automation & Control Systems
Youyang Qu, Shiva Raj Pokhrel, Sahil Garg, Longxiang Gao, Yong Xiang
Summary: Cognitive computing, emulating human brain's reasoning, is flourishing in Industry 4.0, but facing challenges like poisoning attacks and inadequate data resources. A decentralized paradigm for big data-driven cognitive computing (D2C), using federated learning and blockchain, has been proposed to address these challenges effectively. The combination of federated learning and blockchain provides privacy protection, efficient processing, incentive mechanism, and resistance against poisoning attacks.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Automation & Control Systems
Abid Khan, Furqan Shahid, Carsten Maple, Awais Ahmad, Gwanggil Jeon
Summary: Digital twins have been proposed to enhance manufacturing processes, with the goal of benefiting more than 50% of large industries by the end of 2021. However, a common narrative for digital twins is still lacking. To address this, the article presents a detailed framework called spiral DT-framework and suggests using blockchain technology for secure and reliable data management. A new variant of blockchain, called twinchain, is also proposed, which is quantum-resilient and offers immediate transaction confirmation. The article concludes with a framework for deploying twinchain in the manufacturing of a robot surgical machine.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Information Systems
Amrendra Singh Yadav, Nikita Singh, Dharmender Singh Kushwaha
Summary: This article proposes a novel sidechain structure for land/property registry management framework, utilizing blockchain technology to enhance information management, decrease authentication time, and storage consumption. By using mainchain and sidechain, the proposed framework efficiently stores and searches land registry data. It outperforms existing approaches in terms of efficiency.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Interdisciplinary Applications
Tarun Kumar Agrawal, Vijay Kumar, Rudrajeet Pal, Lichuan Wang, Yan Chen
Summary: This study proposes a blockchain-based traceability framework to address information asymmetry and low visibility issues in the textile and clothing industry. The proposed system can build technology-based trust among supply chain partners and offer the opportunity to trace back supply networks and create transparent and sustainable supply chains.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Chemistry, Multidisciplinary
Haotian Chen, Sekione Reward Jeremiah, Changhoon Lee, Jong Hyuk Park
Summary: The Industrial Internet of Things (IIoT) combines smart manufacturing and the Internet of Things, improving product quality and reliability through intelligent connection, real-time data processing, collaborative monitoring, and automatic information processing. This paper proposes an automated smart manufacturing framework based on Digital Twin (DT) and Blockchain, where the data used in DT are from cluster generated after blockchain authentication and only accessed and visualized in the cloud when necessary. Simulation results show that the proposed authentication mode is faster than the standard protocol. Additionally, the DT framework for a smart factory deploys the PDQN DRL model, demonstrating higher accuracy, stability, and reliability.
APPLIED SCIENCES-BASEL
(2023)
Review
Chemistry, Analytical
Xin Guo, Geng Zhang, Yingfeng Zhang
Summary: As a new generation of information technology, blockchain plays a significant role in business and industrial innovation. Its employment in industry has increased transparency, security, traceability, efficiency, and reduced production costs. However, blockchain technology and smart manufacturing have been individually researched. This survey aims to summarize the existing research and provide theoretical foundations for applying blockchain technology to smart manufacturing, creating a more reliable system.
Article
Engineering, Mechanical
Marko Corn, Gregor Cerne, Igor Papic, Maja Atanasijevic-Kunc
STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING
(2014)
Review
Engineering, Mechanical
Nejc Rozman, Marko Corn, Gasper Skulj, Janez Diaci, Primoz Podrzaj
Summary: The study explores scalability solutions in blockchain-supported manufacturing, addressing limitations faced by blockchain networks in terms of scalability, decentralization, and security. Findings suggest that Layer 1 scalability solutions are predominant in general smart manufacturing systems, while Layer 2 scalability solutions are better represented in specific smart manufacturing systems.
STROJNISKI VESTNIK-JOURNAL OF MECHANICAL ENGINEERING
(2022)
Article
Chemistry, Multidisciplinary
Nejc Rozman, Marko Corn, Gasper Skulj, Tomaz Berlec, Janez Diaci, Primoz Podrzaj
Summary: This study investigates the impact of blockchain technology scalability limitations on the performance of Blockchain-Based Shared Manufacturing (BBSM). The findings reveal that a congested blockchain network results in increased transaction costs, reduced service prices, and underutilization of existing maximum production capacities. Allocating funds to financial activities rather than manufacturing activities yields better outcomes for system users. The study highlights the importance of incorporating scalable solutions in blockchain-based manufacturing systems.
APPLIED SCIENCES-BASEL
(2023)
Proceedings Paper
Automation & Control Systems
Nejc Rozman, Rok Vrabic, Marko Corn, Tomaz Pozrl, Janez Diaci
52ND CIRP CONFERENCE ON MANUFACTURING SYSTEMS (CMS)
(2019)
Proceedings Paper
Automation & Control Systems
Marko Corn, Maja Atanasijevic Kunc
Proceedings Paper
Computer Science, Theory & Methods
Marko Corn, Gregor Cerne, Igor Skrjanc, Maja Atanasijevic-Kunc
2013 8TH EUROSIM CONGRESS ON MODELLING AND SIMULATION (EUROSIM)
(2013)
Article
Computer Science, Interdisciplinary Applications
Shenglin Wang, Jingqiong Zhang, Peng Wang, James Law, Radu Calinescu, Lyudmila Mihaylova
Summary: In Industry 5.0, Digital Twins provide flexibility and efficiency for smart manufacturing. Deep learning techniques are used to enhance the Digital Twin framework, enabling the detection and classification of human operators and robots during the manufacturing process. The framework shows promising results in accurately detecting and classifying actions of human operators and robots in various scenarios.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Yi Liu, Junpeng Qiu, Jincheng Wang, Junhe Lian, Zeran Hou, Junying Min
Summary: In this study, a double-sided robotic roller forming process was developed to form ultrahigh strength steels to thin-walled profiles. Synchronized laser heating and iterative path compensation method were used to reduce forming forces and achieve high-precision forming.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Zequn Zhang, Yuchen Ji, Dunbing Tang, Jie Chen, Changchun Liu
Summary: This paper proposes a digital twin system for human-robot collaboration (HRC) that overcomes the limitations of current methods and improves the overall performance. The system includes a human mesh recovery algorithm and uncertainty estimation to enhance the system's capabilities. Experimental results demonstrate the superiority of the proposed methods over baseline methods. The feasibility and effectiveness of the HRC system are validated through a case study involving component assembly.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Junmin Park, Taehoon Kim, Chengyan Gu, Yun Kang, Joono Cheong
Summary: This paper proposes a highly reliable and accurate collision estimator for robot manipulators in human-robot collaborative environments using the Bayesian approach. By assuming robot collisions as dynamic Markov processes, the estimator can integrate prior beliefs and measurements to produce current beliefs in a recursive form. The method achieves compelling performance in collision estimation with high accuracy and no false alarms.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Meng Wang, Kaixuan Chen, Panfeng Wang, Yimin Song, Tao Sun
Summary: In this study, a novel teleoperation machining mode and control strategy were proposed to improve efficiency and accuracy in small batch production of large casting parts. By using variable motion mapping and elastic compensation, constant cutting force was achieved, and the workpiece was protected by employing forbidden virtual fixtures and movement constraints on the slave robot.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhaoyu Li, Dong He, Xiangyu Li, Xiaoke Deng, Pengcheng Hu, Jiancheng Hao, Yue Hou, Hongyu Yu, Kai Tang
Summary: This paper presents a novel algorithm for planning a five-axis inspection path for arbitrary freeform surfaces. By converting the inspection path planning problem into a set-covering problem, the algorithm generates a near-minimum set of inspection paths that satisfy necessary constraints. Both computer simulation and physical inspection experiments confirm the effectiveness and advantages of the proposed method.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hang Zhang, Wenhu Wang, Shusheng Zhang, Yajun Zhang, Jingtao Zhou, Zhen Wang, Bo Huang, Rui Huang
Summary: This paper introduces a novel framework based on deep reinforcement learning for generating machining process routes for designated parts. The framework utilizes graph representations of parts and employs convolutional graph neural networks for effective processing. Experimental results demonstrate the ability of the proposed method to generate efficient machining process routes and overcome limitations of traditional methods.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Regina Kyung-Jin Lee, Hao Zheng, Yuqian Lu
Summary: Future manufacturing will witness a shift towards collaboration and compassion in human-robot relationships. To enable seamless knowledge transfer, a unified knowledge representation system that can be shared by humans and robots is essential. The Human-Robot Shared Assembly Taxonomy (HR-SAT) proposed in this study allows comprehensive assembly tasks to be represented as a knowledge graph that is understandable by both humans and robots. HR-SAT incorporates rich assembly information and has diverse applications in process planning, quality checking, and human-robot collaboration.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Jianhui He, Lefeng Gu, Guilin Yang, Yiyang Feng, Silu Chen, Zaojun Fang
Summary: This paper presents a new modular kinematic error model for collaborative robots and proposes a portable self-calibration device to improve their positioning accuracy.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hongwei Sun, Jixiang Yang, Han Ding
Summary: This paper proposes an asymmetrical FIR filter-based tool path smoothing algorithm to fully utilize the joint drive capability of robot manipulators. The algorithm considers the pose-dependent dynamics and constraints of the robot and improves motion efficiency by over 10% compared to traditional methods.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Dongsheng Ge, Huan Zhao, Yiwei Wang, Dianxi Li, Xiangfei Li, Han Ding
Summary: This paper focuses on learning a stable force control policy from human demonstration during contact transients. Based on the analysis of human demonstration data, a novel human-inspired force control strategy called compliant dynamical system (CDS) is proposed. The effectiveness of the proposed method is validated through simulation and real-world experiments.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Xuepeng Huang, Zhenzhong Wang, Lucheng Li, Qi Luo
Summary: This study models the stiffness of a robot and modifies the tool influence function (TIF) with the Preston equation in order to achieve uniform surface quality in robotic bonnet polishing (RBP) of optical components. Experimental results validate the accuracy of the modified model.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Mario D. Fiore, Felix Allmendinger, Ciro Natale
Summary: This paper presents a constraint-based programming framework for task specification and motion optimization. The framework can handle constraints on robot joint and Cartesian coordinates, as well as time dependency. It also compares with existing methods and provides numerical support through illustrative examples and case studies.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Yongxue Chen, Yaoan Lu, Ye Ding
Summary: This paper presents an optimization method for directly generating a six-degree-of-freedom toolpath for robotic flank milling. By optimizing the smoothness of the toolpath and the stiffness of the robot, the efficiency, accuracy, and finish of the machining are improved.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
Article
Computer Science, Interdisciplinary Applications
Chungang Zhuang, Haoyu Wang, Han Ding
Summary: This article proposes an end-to-end pipeline for synchronously regressing potential object poses from an unsegmented point cloud. It extracts point pair features and uses a voting architecture for instance feature extraction, along with a 3D heatmap for clustering votes and generating center seeds. An attention voting module is also employed to adaptively fuse point-wise features into instance-wise features. The network demonstrates robustness and improved performance in pose estimation.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2024)
