Supporting Digital Production, Product Lifecycle and Supply Chain Management in Industry 4.0 by the Arrowhead Framework – a Survey

Kozma, Dániel; Varga, Pál; Soós, Gábor

doi:10.1109/indin41052.2019.8972216

Cited by 21 publications

(17 citation statements)

References 24 publications

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“…Kozma et al [12] recommended the use of the Arrowhead Framework, a cloud-based solution as a collaboration, combination and control tool within the SCM. Eligible users can share tracking and feedback information.…”

Section: Supply Chain Data Managementmentioning

confidence: 99%

“…The complex global nature of the Supply Chain (SC) presents multiple problems to SCM such as visibility, traceability, scalability, data flow management, trust and associated costs [11]. Industry 4.0, offers an inclusive, holistic approach to SCM through the amalgamation of digital technologies such as DLT, cyberphysical systems (CPS), interconnectivity and access to realtime information to optimize the delivery of goods and services [12], [13]. A digital SC, with activities across the SC becoming much smoother, faster, more transparent, gaining and utilizing insights from real-time information across the entire chain.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Distributed Ledger Technologies in Supply Chain Security Management: A Comprehensive Survey

Asante

Epiphaniou

Maple

et al. 2023

IEEE Trans. Eng. Manage.

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Section: Supply Chain Data Managementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Distributed Ledger Technologies in Supply Chain Security Management: A Comprehensive Survey

Asante

Epiphaniou

Maple

et al. 2023

IEEE Trans. Eng. Manage.

View full text Add to dashboard Cite

“…Digital production, product lifecycle management, and supply chain management are the three pillars of the collaborative European project, Productive4.0 [4]. The Arrowhead Framework [23,24] is used throughout various use-cases here, in order to provide interoperability, integrability and ergonomic engineering capabilities.…”

Section: Industry 40mentioning

confidence: 99%

“…The fourth industrial revolution is underway, with production lines and robots becoming more intelligent. We are able to create robots that download and use the program, which means that the same production line can adapt to an industrial need very quickly [4]. As a high-level example, at one minute, the workstation produces a Type A car, and in the other one it can create a Type B car.…”

Section: Business Impact Of 5gmentioning

confidence: 99%

5G support for Industrial IoT Applications— Challenges, Solutions, and Research gaps

Varga

Pető

Frankó

et al. 2020

Sensors

Self Cite

187

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Industrial IoT has special communication requirements, including high reliability, low latency, flexibility, and security. These are instinctively provided by the 5G mobile technology, making it a successful candidate for supporting Industrial IoT (IIoT) scenarios. The aim of this paper is to identify current research challenges and solutions in relation to 5G-enabled Industrial IoT, based on the initial requirements and promises of both domains. The methodology of the paper follows the steps of surveying state-of-the art, comparing results to identify further challenges, and drawing conclusions as lessons learned for each research domain. These areas include IIoT applications and their requirements; mobile edge cloud; back-end performance tuning; network function virtualization; and security, blockchains for IIoT, Artificial Intelligence support for 5G, and private campus networks. Beside surveying the current challenges and solutions, the paper aims to provide meaningful comparisons for each of these areas (in relation to 5G-enabled IIoT) to draw conclusions on current research gaps.

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“…The Industry4.0 movement [ 1 ] has a huge impact on all manufacturing related fields including logistics and Supply Chain Management (SCM), which are often referred as Logistics 4.0 and SCM 4.0 [ 2 ]. While smart manufacturing considered as the main target of CPS (Cyber-Physical System) based digitization trends; logistics—especially resource planning and warehouse management—and SCM can also derive benefits from inter-twining physical and digital planes.…”

Section: Introductionmentioning

confidence: 99%

Reliable Identification Schemes for Asset and Production Tracking in Industry 4.0

Frankó

Vida

Varga

2020

Sensors

Self Cite

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Revolutionizing logistics and supply chain management in smart manufacturing is one of the main goals of the Industry 4.0 movement. Emerging technologies such as autonomous vehicles, Cyber-Physical Systems and digital twins enable highly automated and optimized solutions in these fields to achieve full traceability of individual products. Tracking various assets within shop-floors and the warehouse is a focal point of asset management; its aim is to enhance the efficiency of logistical tasks. Global players implement their own solutions based on the state of the art technologies. Small and medium companies, however, are still skeptic toward identification based tracking methods, because of the lack of low-cost and reliable solutions. This paper presents a novel, working, reliable, low-cost, scalable solution for asset tracking, supporting global asset management for Industry4.0. The solution uses high accuracy indoor positioning—based on Ultra-Wideband (UWB) radio technology—combined with RFID-based tracking features. Identifying assets is one of the most challenging parts of this work, so this paper focuses on how different identification approaches can be combined to facilitate an efficient and reliable identification scheme.

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Supporting Digital Production, Product Lifecycle and Supply Chain Management in Industry 4.0 by the Arrowhead Framework – a Survey

Cited by 21 publications

References 24 publications

Distributed Ledger Technologies in Supply Chain Security Management: A Comprehensive Survey

Distributed Ledger Technologies in Supply Chain Security Management: A Comprehensive Survey

5G support for Industrial IoT Applications— Challenges, Solutions, and Research gaps

Reliable Identification Schemes for Asset and Production Tracking in Industry 4.0

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