Review
Automation & Control Systems
Georg Weichhart, Herve Panetto, Arturo Molina
Summary: The paper explores the use of new technologies in cyber-physical enterprise systems to support online decision-making based on up-to-date data, with a focus on enterprise interoperability in the manufacturing sector. It highlights the need for interoperability in system-of-systems compared to integration in a single system, and identifies issues arising from insufficient support for the physical aspects of systems. The paper also presents an application scenario from the manufacturing domain to illustrate the developed approach.
ANNUAL REVIEWS IN CONTROL
(2021)
Article
Automation & Control Systems
Yoo Ho Son, Kyu Tae Park, Donggun Lee, Seung Woo Jeon, Sang Do Noh
Summary: The study proposes a digital twin-based cyber-physical system for predicting the feasibility of production plans in automotive body production lines, which was experimentally verified to achieve an average prediction performance of 94.02% for actual production plans. This system provides an advanced solution for predicting production feasibility in automotive manufacturing.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Qiqi Chen, Ming Li, Gangyan Xu, George Q. Huang
Summary: Spare parts management is crucial in aviation MRO, and this paper proposes a Cyber-Physical Spare Parts Intralogistics System (CPSPIS) to address synchronization problems in the SPI business process and resources. It utilizes IoT technologies and unified representations to provide traceability and visibility, while also offering self-X abilities for real-time synchronization. CPSPIS includes communication, tracking and tracing, data source integration, initialization, and self-adjusted execution services, along with applications and visualization tools for real-time cooperation and decision-making.
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Linbei Jiang, Shaohui Su, Xin Pei, Changyong Chu, Yiming Yuan, Kuan Wang
Summary: Digital twin (DT) is a dynamic intelligent system that combines virtual and realistic models with multiple data sources to monitor product operation status and predict product life in smart manufacturing. However, most current DT modeling approaches focus on individual objects and lack modeling approaches for the whole life cycle and multiple objects, hindering the mining and utilization of data from all aspects of products. This paper proposes a part-level DT modeling approach based on PLM/PDM theory, integrating property, process, simulation, and feedback models within a digital thread communication framework.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Engineering, Industrial
T. D. Hedberg, M. E. Sharp, T. M. M. Maw, M. M. Helu, M. M. Rahman, S. Jadhav, J. J. Whicker, A. Barnard Feeney
Summary: The industry seeks a digital thread of information to align different viewpoints such as as-designed, as-planned, as-executed, and as-inspected. A research team conducted an experiment to test the ability of selected open data standards to integrate the lifecycle stages of engineering design, manufacturing, and quality assurance, identifying value for industry even though not all required information could be fully linked.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Tawseef Ayoub Shaikh, Tabasum Rasool, Prabal Verma
Summary: This paper introduces the application of medical cyber-physical systems (MCPS) in healthcare and discusses the relevant technologies and challenges. It also presents the opportunities and challenges that machine intelligence-based MCPS may face in healthcare applications.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2023)
Article
Chemistry, Analytical
Nazik Alturki, Turki Aljrees, Muhammad Umer, Abid Ishaq, Shtwai Alsubai, Oumaima Saidani, Sirojiddin Djuraev, Imran Ashraf
Summary: This research paper investigates the latest trends in safety, security, and privacy related to drones and highlights the importance of secure drone networks. The proposed framework incorporates intelligent machine learning models into the design and structure of IoT-aided drones, rendering adaptable and secure technology to mitigate cyber-security threats.
Article
Automation & Control Systems
Xinghua Gao, Saeid Alimoradi, Jianli Chen, Yuqing Hu, Shu Tang
Summary: Caregivers are traditionally responsible for assisting patients with cognitive decline, but this creates burdens for both caregivers and patients, impacting their quality of life. Ambient Assistive Living (AAL) technologies, incorporating IoT and AI, can play a role in smart buildings by replacing or complementing caregivers and enabling intelligent learning. This review focuses on the intelligence complements provided by smart buildings to enhance the quality of life and autonomy of cognitively declined occupants.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Automation & Control Systems
Mohamed Abdel-Basset, Hossam Hawash, Karam Sallam
Summary: The convergence of industry 4.0 and IoT technologies has made industrial cyber-physical systems more vulnerable to cyber threats. This article proposes a novel federated deep learning model (Fed-TH) that captures the temporal and spatial representations of network data for hunting cyber threats against ICPSs. It also introduces a container-based industrial edge computing framework for deploying the threat-hunting microservice on suitable edge servers, addressing the latency issue of ICPSs.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Information Systems
Yifei Qiu, Shaohua Wu, Ying Wang, Jian Jiao, Ning Zhang, Qinyu Zhang
Summary: This article explores a cyber-physical system with multiple IoT devices, considering edge computing and server processing time. It investigates how to choose the destination of status updates to minimize the overall MSE of the system.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Business
Qianying Gao, Qi Wang, Cisheng Wu
Summary: This study examines the construction of an enterprise digital service and operation platform based on IoT technology. The research finds that asynchronous architecture has higher data processing efficiency compared to synchronous architecture, with a 320% improvement in performance. IoT technology enables intelligent functions through specific devices, sensors, and information processing technologies and is extended and expanded based on the Internet.
JOURNAL OF INNOVATION & KNOWLEDGE
(2023)
Article
Computer Science, Information Systems
Sotirios Brotsis, Konstantinos P. Grammatikakis, Dimitrios Kavallieros, Antonio I. Mazilu, Nicholas Kolokotronis, Konstantinos Limniotis, Costas Vassilakis
Summary: With the increasing number of security incidents targeting the Internet of Things (IoT), IoT forensics has emerged as a branch of digital forensics. This paper proposes the integration of blockchain into IoT forensics to address challenges related to digital evidence authenticity, integrity, confidentiality, and privacy. The proposed blockchain-enabled platform achieves high throughput, low latency, and zero error rate in a realistic smart home environment.
INTERNET OF THINGS
(2023)
Article
Computer Science, Artificial Intelligence
PengYu Wang, Wen-An Yang, YouPeng You
Summary: NC code verification is crucial in CNC machining simulation, and both physical and cyber verification methods have been researched. This study proposes a cyber-physical prototype system using an RGB-D camera to verify NC codes and simulate CNC machining. The system renders virtual workpieces in cyber space for operators to observe in the physical machining scene, demonstrating the feasibility of using computer vision methods in a cyber-physical CNC simulation system.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Chemistry, Multidisciplinary
Mesfer Al Duhayyim, Khalid A. Alissa, Fatma S. Alrayes, Saud S. Alotaibi, ElSayed M. Tag El Din, Amgad Atta Abdelmageed, Ishfaq Yaseen, Abdelwahed Motwakel
Summary: This study introduces a new Stochastic Fractal Search Algorithm with Deep Learning Driven Intrusion Detection System (SFSA-DLIDS) for a cloud-based CPS environment, with a focus on intrusion recognition and classification to enhance security.
APPLIED SCIENCES-BASEL
(2022)
Article
Green & Sustainable Science & Technology
Rafael Gomes Alves, Rodrigo Filev Maia, Fabio Lima
Summary: This paper presents a digital twin model of a smart irrigation system, which utilizes an internet of things platform and a discrete event simulation model to enable automatic data flow and interaction. The system allows farmers to evaluate the behavior and test different irrigation strategies, leading to improvements in agricultural operations and water usage reduction.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Computer Science, Interdisciplinary Applications
Francesco Pistolesi, Michele Baldassini, Beatrice Lazzerini
Summary: More than one in four workers worldwide suffer from back pain, resulting in the loss of 264 million work days annually. In the U.S., it costs $50 billion in healthcare expenses each year, rising up to $100 billion when accounting for decreased productivity and lost wages. The impending Industry 5.0 revolution emphasizes worker well-being and their rights, such as privacy, autonomy, and human dignity. This paper proposes a privacy-preserving artificial intelligence system that monitors the posture of assembly line workers. The system accurately assesses upper-body and lower-body postures while respecting privacy, enabling the detection of harmful posture habits and reducing the likelihood of musculoskeletal disorders.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Xavier Boucher, Camilo Murillo Coba, Damien Lamy
Summary: This paper explores the new business strategies of digital servitization and smart PSS delivery, and develops conceptual prototypes of smart PSS value offers for early stages of the design process. It presents the development and experimentation of a modelling language and toolkit, and applies it to the design of a smart PSS in the field of heating appliances.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Dieudonne Tchuente, Jerry Lonlac, Bernard Kamsu-Foguem
Summary: Artificial Intelligence (AI) is becoming increasingly important in various sectors of society. However, the black box nature of most AI techniques such as Machine Learning (ML) hinders their practical application. This has led to the emergence of Explainable artificial intelligence (XAI), which aims to provide AI-based decision-making processes and outcomes that are easily understood, interpreted, and justified by humans. While there has been a significant amount of research on XAI, there is currently a lack of studies on its practical applications. To address this research gap, this article proposes a comprehensive review of the business applications of XAI and a six-step framework to improve its implementation and adoption by practitioners.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Francois-Alexandre Tremblay, Audrey Durand, Michael Morin, Philippe Marier, Jonathan Gaudreault
Summary: Continuous high-frequency wood drying, integrated with a traditional wood finishing line, improves the value of lumber by correcting moisture content piece by piece. Using reinforcement learning for continuous drying operation policies outperforms current industry methods and remains robust to sudden disturbances.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Luyao Xia, Jianfeng Lu, Yuqian Lu, Wentao Gao, Yuhang Fan, Yuhao Xu, Hao Zhang
Summary: Efficient assembly sequence planning is crucial for enhancing production efficiency, ensuring product quality, and meeting market demands. This study proposes a dynamic graph learning algorithm called assembly-oriented graph attention sequence (A-GASeq), which optimizes the assembly graph structure to guide the search for optimal assembly sequences. The algorithm demonstrates superiority and broad utility in real-world scenarios.
COMPUTERS IN INDUSTRY
(2024)
Article
Computer Science, Interdisciplinary Applications
Mutahar Safdar, Padma Polash Paul, Guy Lamouche, Gentry Wood, Max Zimmermann, Florian Hannesen, Christophe Bescond, Priti Wanjara, Yaoyao Fiona Zhao
Summary: Metal-based additive manufacturing can achieve fully dense metallic components, and the application of machine learning in this field has been growing rapidly. However, there is a lack of framework to manage these machine learning models and guidance on the fundamental requirements for a cross-disciplinary platform to support process-based machine learning models in industrial metal AM.
COMPUTERS IN INDUSTRY
(2024)