Article
Green & Sustainable Science & Technology
Jiri Vyskocil, Petr Douda, Petr Novak, Bernhard Wally
Summary: Industry 4.0 smart production systems require integrated industrial systems and subsystems that support high modularity and reconfigurability. This article presents an MES architecture that autonomously composes, verifies, interprets, and executes production plans using digital twins and symbolic planning methods. The proposed solution allows for on-the-fly replanning and distributed operation with multiple instances, all synchronized in real-time.
Article
Engineering, Electrical & Electronic
Greyce N. Schroeder, Charles Steinmetz, Ricardo Nagel Rodrigues, Renato Ventura Bayan Henriques, Achim Rettberg, Carlos Eduardo Pereira
Summary: The digital twin is a virtual representation of physical objects that can predict and optimize the behavior of production systems, using a design methodology based on MDE. It includes modeling at two levels, a generic reference architecture and a concrete implementation methodology, all of which are validated through a case study.
PROCEEDINGS OF THE IEEE
(2021)
Review
Construction & Building Technology
Wei Hu, Kendrik Yan Hong Lim, Yiyu Cai
Summary: Digital twins (DT) are cost-effective solutions that have gained popularity in the building and construction industry. This paper conducts a systematic literature review to evaluate the advantages of DT systems from the perspectives of Industry 4.0 technologies, project management, and building lifecycle, and proposes future directions for their development.
Article
Engineering, Industrial
Wenjun Xu, Jia Cui, Lan Li, Bitao Yao, Sisi Tian, Zude Zhou
Summary: This paper introduces the application of digital twin technology in the field of industrial cloud robotics, encapsulating robot control capabilities as cloud services and implementing fine sensing control of physical manufacturing systems using digital twin technology. This technology is capable of synchronizing and merging digital models with physical robots to achieve accurate control, and it has flexibility and scalability by utilizing ontology models.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Dan Li, Asa Fast-Berglund, Dan Paulin, Peter Thorvald
Summary: This paper discusses the importance of providing digital information support technology for Operator 4.0 in the transformation towards Industry 4.0, and explores how these technologies can improve operators' efficiency and adaptability to complex production environments through five industrial cases.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Chemistry, Multidisciplinary
Oussama H. Hamid
Summary: In recent years, data-centric AI has gained popularity over model-centric AI due to its different focus. This paper reconciles the two approaches and highlights the limitations of model-centric AI in terms of algorithmic stability and robustness.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Interdisciplinary Applications
Jyrki Savolainen, Mikkel Stein Knudsen
Summary: This paper discusses the value proposition of a system-level Digital Twin (DT) from a managerial perspective in complex manufacturing processes. It highlights the gap between the vision of digital twin technology and what is currently feasible within existing industrial infrastructure. The research suggests that large system-level DT projects only make managerial sense when certain preliminary conditions are met and fulfilled.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2022)
Article
Computer Science, Information Systems
Yuk Ming Tang, Wei Ting Kuo, C. K. M. Lee
Summary: Real-time object recognition and inspection based on AI is crucial in the digital era, and the establishment of digital twins can promote the integration of physical machines and the digital space. In order to achieve digital twinning for object recognition and human-machine interaction, we proposed a DT architecture that integrates the latest Mixed Reality device for real-time data streaming.
INTERNET OF THINGS
(2023)
Article
Chemistry, Multidisciplinary
Domenico Buongiorno, Donato Caramia, Luca Di Ruscio, Nicola Longo, Simone Panicucci, Giovanni Di Stefano, Vitoantonio Bevilacqua, Antonio Brunetti
Summary: The demand for robot-based depalletization systems has been increasing in recent years due to the growth of logistics, storage, and supply chain sectors. Classical depalletization systems are being replaced by innovative solutions based on 2D/3D vision and deep learning methods to handle unstructured scenarios. This study compares different training strategies to customize an object detection model and validates the effectiveness of fine-tuning a pre-trained CNN model for this task.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Industrial
Bzhwen A. Kadir, Ole Broberg
Summary: This paper proposes a framework that combines human factors and ergonomics, work system modeling, and strategy design for (re)designing industrial work systems in the transition towards Industry 4.0. The framework has been tested through ten retrospective case studies and a collaborative workshop in an industrial company, showing its applicability and effectiveness.
APPLIED ERGONOMICS
(2021)
Article
Computer Science, Information Systems
Xinzheng Feng, Jun Wu, Yulei Wu, Jianhua Li, Wu Yang
Summary: The deployment of edge AI aggravates the complexity and security risks in the Industrial Internet of Things (IIoT) for intelligent digital factories. To address this, a trustworthy self-healing scheme based on distributed digital twin (DT) and blockchain is proposed. The scheme includes an implementation architecture for the self-healing IIoT using distributed DT simulation capability, a DT simulation operating mechanism for industrial devices, and a blockchain-based decentralized trust management mechanism. Security analysis and performance evaluation demonstrate the security and efficiency of the proposed scheme.
INFORMATION SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Ting Yu Lin, Zhengxuan Jia, Chen Yang, Yingying Xiao, Shulin Lan, Guoqiang Shi, Bi Zeng, Heyu Li
Summary: This paper proposes a new mode based on evolutionary digital twin (EDT), which establishes a more precise approximate model through supervised learning and conducts collaborative exploration in multiple cyberspaces through reinforcement learning, bringing more flexibility and adaptability to intelligent industrial products through machine learning.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Engineering, Electrical & Electronic
Vatsal Maru, Saideep Nannapaneni, Krishna Krishnan, Ali Arishi
Summary: This paper presents an intelligent cyber-physical system framework that combines image processing and deep-learning techniques to improve production efficiency and ensure human safety in real-time operations. The framework utilizes a CNN-based object detection and control analysis approach, and employs real-time data exchange protocol for communication between the detected objects and the actuation system. The proposed framework is demonstrated in object detection-based pick-and-place operations, which are widely performed in quality control and industrial systems. The paper also discusses the importance of latency in communication and introduces a Bayesian approach for uncertainty quantification to design a reliable communication framework.
Article
Multidisciplinary Sciences
Armando Walter Colombo, Stamatis Karnouskos, Christoph Hanisch
Summary: The digital transformation in industry requires the establishment of an industrial network based on service cooperation between digital assets and humans, leading to a fundamental shift in mindset. The digitization process along the three dimensions of the Industry 4.0 reference architecture model is crucial for achieving digital transformation.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2021)
Review
Chemistry, Analytical
Ziqi Huang, Yang Shen, Jiayi Li, Marcel Fey, Christian Brecher
Summary: Digital twin and artificial intelligence technologies play essential roles in Industry 4.0, with a focus on the integration of infrastructure, algorithms, and applications. AI-driven digital twin technologies are widely used in smart manufacturing and advanced robotics, offering advantages for sustainable development.
Article
Mechanics
Kilian Grundl, Thorsten Schindler, Heinz Ulbrich, Daniel J. Rixen
MULTIBODY SYSTEM DYNAMICS
(2019)
Article
Automation & Control Systems
Johannes Schmitt, Thomas Gamer, Marie Platenius-Mohr, Somayeh Malakuti, Soeren Finster
AT-AUTOMATISIERUNGSTECHNIK
(2019)
Article
Automation & Control Systems
Thomas Gamer, Mario Hoernicke, Benjamin Kloepper, Reinhard Bauer, Alf J. Isaksson
JOURNAL OF PROCESS CONTROL
(2020)
Review
Chemistry, Analytical
Martin W. Hoffmann, Stephan Wildermuth, Ralf Gitzel, Aydin Boyaci, Joerg Gebhardt, Holger Kaul, Ido Amihai, Bodo Forg, Michael Suriyah, Thomas Leibfried, Volker Stich, Jan Hicking, Martin Bremer, Lars Kaminski, Daniel Beverungen, Philipp zur Heiden, Tanja Tornede
Article
Instruments & Instrumentation
Joerg Gebhardt, Guruprasad Sosale, Subhashish Dasgupta
TM-TECHNISCHES MESSEN
(2020)
Article
Engineering, Chemical
Jochen Schmid, Katrin Teichert, Moncef Chioua, Thorsten Schindler, Michael Bortz
CHEMIE INGENIEUR TECHNIK
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Thomas Gamer, Johannes O. Schmitt, Roland Braun, Alexander M. Schramm
INTELLIGENT COMPUTING, VOL 1
(2019)
Proceedings Paper
Engineering, Electrical & Electronic
Arda Tueysuez, Thorsten Schindler, Christian Simonidis, Christian Reuber
2019 IEEE 13TH INTERNATIONAL CONFERENCE ON POWER ELECTRONICS AND DRIVE SYSTEMS (PEDS)
(2019)
Proceedings Paper
Engineering, Industrial
Thomas Gamer, Benjamin Kloepper, Mario Hoernicke
45TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY (IECON 2019)
(2019)
Proceedings Paper
Automation & Control Systems
Thomas Gamer, Mario Hoernicke, Benjamin Kloepper, Reinhard Bauer, Alf J. Isaksson
