Manufacturing Blockchain of Things for the Configuration of a Data- and Knowledge-Driven Digital Twin Manufacturing Cell

Zhang, Chao; Zhou, Guanghui; Han, Ling; Cao, Yan

doi:10.1109/jiot.2020.3005729

Cited by 109 publications

(67 citation statements)

References 44 publications

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“…It aims to implement solutions for using fast-enough 3D-capture devices to acquire moving objects or articulated machinery and then streaming this 3D information into a virtual environment to facilitate planning tasks (Akpan and Brooks 2012). The technologies explained above and others including virtual reality, augmented reality, and digital twin can be deployed in various applications to extract data from sensors for analysis and visualization (Zhang et al 2020;Akpan 2010;Dangelmaier et al 2005;Akpan and Shanker 2017). This practice enhances design, manufacturing, and speed to market.…”

Section: Artificial Intelligencementioning

confidence: 99%

Small business awareness and adoption of state-of-the-art technologies in emerging and developing markets, and lessons from the COVID-19 pandemic

Akpan

Udoh²,

Adebisi

2020

Journal of Small Business & Entrepreneurship

298

164

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Many challenges continue to hinder digital technologies' adoption by small and medium scale enterprises (SMEs) in developing economies. Comparatively, there are more success stories by SMEs in emerging markets. However, most SMEs operating in the informal sector in the emerging markets and developing economies (EMDEs) face similar challenges that inhibit the adoption of advanced technologies and innovations needed to improve business operations and re-engineer processes. This article evaluates the implementation and use of state-of-the-art technologies by SMEs in EMDEs to improve operations performance and create sustainable competitive advantages. Further, the papers in this Special Issue identify FinTech and analytical algorithms as some of the current technologies employed by SMEs in EMDEs to improve operations and processes in the manufacturing and service industries. The recognized technologies and technical innovations that seem novel in EMDEs have long existed in the advanced economies. Most state-of-the-art technologies, including cloud computing, 'big data', and predictive analytics that can improve operations and strategic decisions, are yet to make inroads in most EMDEs. Also, disruptive computing technologies, data analytics, and the Internet of Things (IoT) required to engineer new business models, reduce overheads, enhance competitive advantages, and digitize SMEs' business operations remain untapped. The absence and non-adoption of digital technologies in EMDEs explain why business activities in most EMDEs remain shut during the outbreak of SARS-CoV-2 and the community lockdown to contain the COVID-19 pandemic. The strategies to survive the 'new normal' imposed by COVID-19 and fierce global competition includes a successful adoption of advanced technologies. RÉSUMÉ De nombreux d efis continuent a entraver l'adoption des technologies num eriques par les petites et les moyennes entreprises (PME) dans les economies en d eveloppement. En comparaison, les PME ont plus de succ es dans les march es emergents. Cependant, la plupart de celles qui op erent dans le secteur informel des march es emergents et des economies en d eveloppement (MEED)

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Section: Artificial Intelligencementioning

confidence: 99%

Small business awareness and adoption of state-of-the-art technologies in emerging and developing markets, and lessons from the COVID-19 pandemic

Akpan

Udoh²,

Adebisi

2020

Journal of Small Business & Entrepreneurship

298

164

View full text Add to dashboard Cite

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“…DT is becoming an important technology when mapping physical space to cyber space in DT enhanced human-machine interface, so as to optimize the decision-making ability of production management or smart manufacturing [12]. The CPS interface can be used for data insertion and data visualization during digital twinning in a data-driven way [13]. Based on DT enhanced simulations in CPS, environment factors and human behaviors can be effectively regulated during the manufacturing process.…”

Section: A Dt Technology In Cpsmentioning

confidence: 99%

Intelligent Small Object Detection for Digital Twin in Smart Manufacturing With Industrial Cyber-Physical Systems

Zhou

Liang

et al. 2022

IEEE Trans. Ind. Inf.

209

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Recently, along with several technological advancements in Cyber-Physical Systems (CPS), the revolution of Industry 4.0 has brought in an emerging concept named Digital Twin (DT), which shows it potential to break the barrier between the physical and cyber space in smart manufacturing. However, it is still difficult to analyze and estimate the real-time structural and environmental parameters in terms of their dynamic changes in digital twinning, especially when facing detection tasks of multiple small objects from a large-scale scene with complex contexts in modern manufacturing environments. In this study, we focus on a small object detection model for DT (SOD-DT), aiming to realize the dynamic synchronization between a physical manufacturing system and its virtual representation. Three significant elements, including equipment, product, and operator, are considered as the basic environmental parameters to represent and estimate the dynamic characteristics and real-time changes in building a generic DT system of smart manufacturing workshop. A hybrid deep neural network model based on the integration of MobileNetv2, YOLOv4, and Openpose, is constructed to identify the real-time status from physical manufacturing environment to virtual space. A learning algorithm is then developed to realize the efficient multi-type small object detection based on the feature integration and fusion from both shallow and deep layers, in order to facilitate the modeling, monitoring, and optimizing of the whole manufacturing process in DT system. Experiments and evaluations conducted in

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“…The Makerchain model has used DTs to synchronize the updating of data tags and ensure the personalized demands to make manufacturing service transactions among makers more trustworthy. In [39], the authors have proposed a manufacturing blockchain of things (MBCoT) architecture for secure, traceable, and decentralized manufacturing configuration. The authors have defined the data-and knowledge-driven DT manufacturing cell as a reference model for decentralized manufacturing.…”

Section: Digital Twins and Blockchainmentioning

confidence: 99%

Blockchain-Empowered Digital Twins Collaboration: Smart Transportation Use Case

et al. 2021

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Digital twins (DTs) is a promising technology in the revolution of the industry and essential for Industry 4.0. DTs play a vital role in improving distributed manufacturing, providing up-to-date operational data representation of physical assets, supporting decision-making, and avoiding the potential risks in distributed manufacturing systems. Furthermore, DTs need to collaborate within distributed manufacturing systems to predict the risks and reach consensus-based decision-making. However, DTs collaboration suffers from single failure due to attack and connection in a centralized manner, data interoperability, authentication, and scalability. To overcome the above challenges, we have discussed the major high-level requirements for the DTs collaboration. Then, we have proposed a conceptual framework to fulfill the DTs collaboration requirements by using the combination of blockchain, predictive analysis techniques, and DTs technologies. The proposed framework aims to empower more intelligence DTs based on blockchain technology. In particular, we propose a concrete ledger-based collaborative DTs framework that focuses on real-time operational data analytics and distributed consensus algorithms. Furthermore, we describe how the conceptual framework can be applied using smart transportation system use cases, i.e., smart logistics and railway predictive maintenance. Finally, we highlighted the future direction to guide interested researchers in this interesting area.

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Manufacturing Blockchain of Things for the Configuration of a Data- and Knowledge-Driven Digital Twin Manufacturing Cell

Cited by 109 publications

References 44 publications

Small business awareness and adoption of state-of-the-art technologies in emerging and developing markets, and lessons from the COVID-19 pandemic

Small business awareness and adoption of state-of-the-art technologies in emerging and developing markets, and lessons from the COVID-19 pandemic

Intelligent Small Object Detection for Digital Twin in Smart Manufacturing With Industrial Cyber-Physical Systems

Blockchain-Empowered Digital Twins Collaboration: Smart Transportation Use Case

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