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

Perno, Matteo; Hvam, Lars; Haug, Anders

doi:10.1016/j.compind.2021.103558

Cited by 143 publications

(85 citation statements)

References 93 publications

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“…They aim at determining the relationship between AI, ML, big data, IoT and DTs, as well as the tools required for the creation of AI-enabled DT and the criteria to build successful DT-based systems. Perno et al [ 127 ] also survey enabling technologies of DTs and the existing barriers or limitations that they create to continue developing DT. These topics are out of the scope of this paper.…”

Section: Discussionmentioning

confidence: 99%

Design, Modeling and Implementation of Digital Twins

Segovia

García-Alfaro

2022

Sensors

125

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A Digital Twin (DT) is a set of computer-generated models that map a physical object into a virtual space. Both physical and virtual elements exchange information to monitor, simulate, predict, diagnose and control the state and behavior of the physical object within the virtual space. DTs supply a system with information and operating status, providing capabilities to create new business models. In this paper, we focus on the construction of DTs. More specifically, we focus on determining (methodologically) how to design, create and connect physical objects with their virtual counterpart. We explore the problem into several phases: from functional requirement selection and architecture planning to integration and verification of the final (digital) models. We address as well how physical components exchange real-time information with DTs, as well as experimental platforms to build DTs (including protocols and standards). We conclude with a discussion and open challenges.

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Section: Discussionmentioning

confidence: 99%

Design, Modeling and Implementation of Digital Twins

Segovia

García-Alfaro

2022

Sensors

125

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“…It has distinct parts that are related to each other to fulfill their collective mission. Since the software is enabled by many components, the digital twin boundary could be unclear [39]. This happens due to the extension of the digital twin in the manufacturing system [40].…”

Section: Resultsmentioning

confidence: 99%

Analyzing the Implementation of a Digital Twin Manufacturing System: Using a Systems Thinking Approach

Loaiza

Cloutier

2022

Systems

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Digital twin (DT) is a technology that promises great benefits for the manufacturing industry. Nevertheless, DT implementation presents many challenges. This article looks to understand and study the problems associated with the implementation of DT models in a manufacturing domain. It applies systems thinking techniques to analyze and refine these problems. Systems thinking presents several methods and tools that help in studying a problem space and a solution space. The conceptagon framework describes the DT model as a system with several attributes and analyzes it in detail. A systemigram shows the relationship of manufacturing systems and the DT model. It maps the processes and components for DT implementation. The TRIZ method analyzes, and forecasts problems related to DT development and provides solutions based on patterns of invention. The CATWOE analysis allows identification of stakeholders and the study of the DT model from their perspectives. It provides a root definition of the DT model to refine a problem and the problem’s contradiction. The 9 windows tool helps to delimit the DT implementation problem, based on time and space. It gives eight more perspectives to solve the DT problem. Finally, the ideal final result (IFR) method provides the ideal DT model concept for manufacturing systems.

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“…The envisioned operations incorporate (i) a novel self-learning distributed approach; (ii) a data-and knowledge-driven approach for digital twin manufacturing towards intelligent energy management in manufacturing; (iii) novelty in modelling algorithms and finally (iv) a novel, thorough industrial model-based management system to help humans to resolve unforeseen critical situations in smart factories towards (1) efficient production planning to reduce energy consumption, costs, and the relevant environmental footprints, (2) effective analysis and improvement of production processes towards the same direction. Environmental barriers affect organizational factors, which in turn have an impact on system integration, system and data security, and data quality [57].…”

Section: Discussionmentioning

confidence: 99%

An Equifinality Energy Management Framework in Terms of Benchmarking Practices and Expectations: The EnerMan Project Outlook

Katrakazas¹,

Costantino

Magnea

et al. 2021

Systems

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Background: The Industry 4.0 wave is leading the changes in existing manufacturing and industrial processes across the world. This is especially important in the formulation of the smart-factory concept with an outlook to energy sustainable processes. In viewing and identifying the foundational elements of such a transformation, the initial conditions and current practices in a cross-sectoral manner is considered a first, yet crucial step in the EU-funded project EnerMan. Methods: In this paper, we identify and analyse the key common features and characteristics of industrial practices set in a perspective of similar and identical functions with a focus to three key energy areas: sustainability, management, and footprint. The examination of different industrial sector cases is performed via distributed questionnaires and then viewed under the prism of the equifinality state via a text-mining analysis approach. Results: identification of common themes and benchmarking of current practices in a cross-industry manner led to the creation of a common systemic framework within energy management related aspects, which is hereby presented. Conclusions: use of an equifinality approach in energy management practices should be further pursued to open up new methods of ideation and innovation and communicate systems’ design in tandem with each industrial set goals.

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

Cited by 143 publications

References 93 publications

Design, Modeling and Implementation of Digital Twins

Design, Modeling and Implementation of Digital Twins

Analyzing the Implementation of a Digital Twin Manufacturing System: Using a Systems Thinking Approach

An Equifinality Energy Management Framework in Terms of Benchmarking Practices and Expectations: The EnerMan Project Outlook

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