Modeling and implementation of a digital twin of material flows based on physics simulation

Glatt, Moritz; Sinnwell, Chantal; Yi, Li; Donohoe, Sean P.; Ravani, Bahram; Aurich, Jan C.

doi:10.1016/j.jmsy.2020.04.015

Cited by 103 publications

(32 citation statements)

References 39 publications

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“…An increasing number of vendors are developing and offering unified IoT/IIoT platforms and solutions designed to be compatible with existing systems . To overcome the challenge of integration between legacy systems and new IoT/IIoT systems for the realization of DTs in industrial applications (Rolle et al, 2019;Borangiu et al, 2020), vendor-neutral communication protocols such as OPC-UA are being used (Redelinghuys et al, 2020;Glatt et al, 2021).…”

Section: Connecting Barriers and Enablersmentioning

confidence: 99%

Implementation of digital twins in the process industry: A systematic literature review of enablers and barriers

Perno

Hvam

Haug

2022

Computers in Industry

148

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Since the introduction of the concept of "digital twins" (DTs) in 2002, the number of practical applications in different industrial sectors has grown rapidly. Despite the hype surrounding this technology, companies face significant challenges upon deciding to implement DTs in their organizations due to the novelty of the concept. Furthermore, little research on DT has been conducted for the process industry, which may be explained by the high complexity of accurately representing and modeling the physics behind production processes. To consolidate the fragmented literature on the enabling factors and challenges in DT implementation in the process industry, this study organizes the existing studies on DTs with a focus on barriers and enablers. On this basis, this study contributes to the existing body of knowledge on DTs by organizing the DT literature and by proposing conceptual models describing enablers of and barriers to DT implementation, as well as their mutual relationships.

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Section: Connecting Barriers and Enablersmentioning

confidence: 99%

Implementation of digital twins in the process industry: A systematic literature review of enablers and barriers

Perno

Hvam

Haug

2022

Computers in Industry

148

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“…In the digital twin concept, such smart devices collect data and transmit it to the virtual representation in the cloud, but also vice versa to optimize the physical product state based on analytics conducted on the virtual model [23]. Digital twins are understood and adopted as one of the key enablers for digital transformation in the manufacturing industry [23,31,[33][34][35].…”

Section: Digital Building Twinsmentioning

confidence: 99%

Digital Building Twins and Blockchain for Performance-Based (Smart) Contracts

Hunhevicz

Motie

Hall

2021

Blockchain and the Digital Twin

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Performance contracts used for servitized business models enable consideration of overall life-cycle costs rather than just production costs. However, practical implementation of performance contracts has been limited due to challenges with performance evaluation, accountability, and financial concepts. As a solution, this paper proposes the connection of the digital building twin with blockchain-based smart contracts to execute performance-based digital payments. First, we conceptualize a technical architecture to connect blockchain to digital building twins. The digital building twin stores and evaluates performance data in real-time while the blockchain ensures transparency and trusted execution of automatic performance evaluation and rewards through smart contracts. Next, we demonstrate the feasibility of both the concept and technical architecture by integrating the Ethereum blockchain with digital building models and sensors via the Siemens building twin platform. The resulting prototype is the first full-stack implementation of a performance-based smart contract in the built environment.

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“…The main advantage of a DT is that it can accurately model a complex system without interacting with it, which would otherwise be costly in the physical world. DT examples include enabling smart manufacturing in Industry 4.0 [2], improving the performance and design of complex engineering products (e.g., engine design ) or modelling physical interactions [3].…”

Section: Introductionmentioning

confidence: 99%

Digital Twin Network: Opportunities and Challenges

Almasan¹,

Ferriol-Galmés²,

Paillissé³

et al. 2022

Preprint

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The proliferation of emergent network applications (e.g., AR/VR, telesurgery, real-time communications) is increasing the difficulty of managing modern communication networks. These applications typically have stringent requirements (e.g., ultra-low deterministic latency), making it more difficult for network operators to manage their network resources efficiently. In this article, we propose the Digital Twin Network (DTN) as a key enabler for efficient network management in modern networks. We describe the general architecture of the DTN and argue that recent trends in Machine Learning (ML) enable building a DTN that efficiently and accurately mimics real-world networks. In addition, we explore the main ML technologies that enable developing the components of the DTN architecture. Finally, we describe the open challenges that the research community has to address in the upcoming years in order to enable the deployment of the DTN in real-world scenarios.

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Modeling and implementation of a digital twin of material flows based on physics simulation

Cited by 103 publications

References 39 publications

Implementation of digital twins in the process industry: A systematic literature review of enablers and barriers

Implementation of digital twins in the process industry: A systematic literature review of enablers and barriers

Digital Building Twins and Blockchain for Performance-Based (Smart) Contracts

Digital Twin Network: Opportunities and Challenges

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