A Digital Twin-Based Heuristic Multi-Cooperation Scheduling Framework for Smart Manufacturing in IIoT Environment

Chen, Haotian; Jeremiah, Sekione Reward; Lee, Chang‐Hoon; Park, Jong Hyuk

doi:10.3390/app13031440

Cited by 22 publications

(5 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The most widely used approach to provide privacy and security in the Digital Twin ecosystem in the existing literature is Blockchain (Smart Contract) technology. In [46,15,71,73,72,70] Blockchain-based data transmission scheme for data integrity are proposed. Due to the inherent nature of Blockchain, the proposed solution based on this technology has a limitation in providing data confidentiality.…”

Section: Security Mechanisms Analysis From Literaturementioning

confidence: 99%

See 1 more Smart Citation

Systematic Literature Review: Digital Twins’ Role in Enhancing Security for Industry 4.0 Applications

El-Hajj,

Gebremariam,

Itapelo

2024

Preprint

View full text Add to dashboard Cite

Connectivity and data exchange are key features of Industry 4.0. In this paradigm, (Industrial) Internet of Things ((I)IoT) devices are a vital component facilitating the collection and transmission of environmental data from the physical sys- tem to the central station for processing and analysis(Digital Twin). However, although (I)IoT devices play a critical role in this process, they are not inherently equipped to run strong encryption mechanisms to secure the data they transmit over wired or wireless channels. This research aims to explore the potential of Digital Twins (DT) in securing Industry 4.0 appli- cations and the security mechanism employed to ensure con- fidentiality, integrity, and authentication of data communi- cated between (I)IoT and DT through a Systematic Literature Review (SLR). This systematic literature review, based on the analysis of 67 papers published between 2018 and 2023, un- derscores the evolving significance of Digital Twin technol- ogy, particularly within the ambit of Industry 4.0. The find- ings illuminate the pervasive influence of Digital Twin tech- nology across multiple industrial sectors. The result SLR re- vealed that DT is growing and being widely adopted as a se- curity tool particularly in Industry 4.0 using enabling tech- nology like machine learning, data analytics, blockchain, and 5G networks to provide security solutions such as intrusion detection, vulnerability assessment, cyber range, and threat intelligence.

show abstract

Section: Security Mechanisms Analysis From Literaturementioning

confidence: 99%

“…The authors in [70] proposed a secure smart manufacturing framework through the integration of Digital Twin (DT) and Blockchain technologies. The framework aimed to facilitate efficient and secure multi-party collaborative information processing in heterogeneous IIoT environments.…”

mentioning

confidence: 99%

Systematic Literature Review: Digital Twins’ Role in Enhancing Security for Industry 4.0 Applications

El-Hajj,

Gebremariam,

Itapelo

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The establishment of a DT model typically involves digitizing, connecting, and continuously updating representations of physical equipment. The entire application process can be delineated into steps such as data collection, data transmission, data processing, and model updates, ensuring synchronization between the DT and the actual physical systems (Chen et al, 2023a).…”

Section: Industrial Internet Of Things and Digital Twinmentioning

confidence: 99%

IoT Real-Time Production Monitoring and Automated Process Transformation in Smart Manufacturing

Wang,

Hu,

Wang

et al. 2024

Journal of Organizational and End User Computing

View full text Add to dashboard Cite

Conventional automobile manufacturing plants involve intricate assembly, testing, and debugging processes heavily reliant on manual operations. This study aims to explore the application of industrial internet of things (IIoT) and deep learning algorithms to achieve process automation in manufacturing. Firstly, utilizing IIoT technology, OPC UA, and point cloud fitting techniques, a comprehensive modeling of most equipment and materials within the factory is conducted, constructing a digital twin (DT) model as a virtual representation of actual equipment. Subsequently, the study innovatively introduces the deep Q network algorithm, facilitating the automatic transition of the production process and improving production efficiency. Through comparison with ten baseline models, the proposed model demonstrates an improvement in production efficiency of at least four percentage points compared to other models. Experimental validation confirms the effectiveness of the proposed model in the smart factory for electric vehicle manufacturing.

show abstract

“…IoT technologies can be applied to various aspects of production, including supply chain [7], scheduling [8], inventory management [9], assembly [10], and quality control [11]. One significant application is real-time monitoring and control of production processes [12].…”

Section: Internet Of Things (Iot)mentioning

confidence: 99%

A production interface to enable legacy factories for industry 4.0

Kwok,

Gaasenbeek

2023

Eng. Res. Express

View full text Add to dashboard Cite

Due to the recent pandemic, our factory operations have experienced significant setbacks, prompting the need for factory automation to maintain productivity. However, most of our factories rely heavily on human input and oversight and cannot operate remotely. Automating our factories has revealed technological gaps that fall short of our expectations, needs, and vision. Therefore, the purpose of this paper is to bridge this gap by introducing practical methodologies and applied technology that can enhance legacy factories and their equipment. Our proposed solution is the ORiON Production Interface (OPI) unit, which can function as a smart networked edge device for virtually any machine, allowing the factory to operate efficiently. We have incorporated various computer vision algorithms into the OPI unit, enabling it to autonomously detect errors, make decentralized decisions, and control quality. Despite the concept of Industry 4.0 (I4.0) being known, many machines in use today are closed source and unable to communicate or join a network. Our research offers a viable solution to implement Industry 4.0 in existing factories, and experimental results have demonstrated various applications such as process monitoring, part positioning, and broken tool detection. Our intelligent networked system is novel and enables factories to be more innovative and responsive, ultimately leading to enhanced productivity. All manufacturing companies interested in adopting Industry 4.0 technology can benefit from it, and the OPI, being an IoT device, is also an appealing option for developers and hobbyists alike.

show abstract

A Digital Twin-Based Heuristic Multi-Cooperation Scheduling Framework for Smart Manufacturing in IIoT Environment

Cited by 22 publications

References 25 publications

Systematic Literature Review: Digital Twins’ Role in Enhancing Security for Industry 4.0 Applications

Systematic Literature Review: Digital Twins’ Role in Enhancing Security for Industry 4.0 Applications

IoT Real-Time Production Monitoring and Automated Process Transformation in Smart Manufacturing

A production interface to enable legacy factories for industry 4.0

Contact Info

Product

Resources

About