Digital Twin for Smart Manufacturing: The Simulation Aspect

Shao, Guodong; Jain, Sanjay; Laroque, Christoph; Lee, Loo Hay; Lendermann, Peter; Rose, Oliver

doi:10.1109/wsc40007.2019.9004659

Cited by 58 publications

(20 citation statements)

References 22 publications

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“…Among these, simulation is by far the most commonly referenced in the literature, as it is at the core of the DT concept . In fact, many researchers and industry practitioners refer to the two concepts interchangeably (Shao, 2019). An important topic of debate in the literature is the advantages and disadvantages of building DTs using expensive software platforms provided by large software providers (e.g., Honeywell, Microsoft, General Electrics, Siemens) as opposed to using open-source software (Damjanovic-Behrendt and Behrendt, 2019).…”

Section: Categorization Of Dt 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

146

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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: Categorization Of Dt 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

146

View full text Add to dashboard Cite

show abstract

“…A specific class or type of DT commonly has a specific objective (e.g., process optimization), pre-definition of operation environment (e.g., equipment, process, and other context), and defined methods or guidelines for development and deployment. • DTs such as general equipment and software simulators are also available, with their purpose less directed (i.e., the capability being improved is not as succinctly specified, is not directly considered in the design of the simulator, or the capability is one of many to which the simulator can be configured to address), and capability boundaries usually not as well-defined [48]. These DTs are generally not used during actual manufacturing (e.g., they might be used for off-line analysis or planning); however, DTs that are more dedicated to a specific purpose, as described above, might be built from specific configurations using the general simulators and then applied during manufacturing.…”

Section: B Dt Uses Today and Current Trendsmentioning

confidence: 99%

“…Approaches for designing production lines utilizing DTs for optimizing system performance are proposed in the literature [60], [61], [39], [40], [32], [19]. Similarly, the perspective of simulation for current and future DTs is discussed in [48].…”

Section: Dts Of the Future: Near-term And Longer-termmentioning

confidence: 99%

A Requirements Driven Digital Twin Framework: Specification and Opportunities

et al. 2020

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Among the tenets of Smart Manufacturing (SM) or Industry 4.0 (I4.0), digital twin (DT), which represents the capabilities of virtual representations of components and systems, has been cited as the biggest technology trend disrupting engineering and design today. DTs have been in use for years in areas such as model-based process control and predictive maintenance, however moving forward a framework is needed that will support the expected pervasiveness of DT technology in the evolution of SM or I4.0. A set of requirements for a DT framework has been derived from analysis of DT definitions, DTs in use today, expected DT applications in the near future, and longer-term DT trends and the DT vision in SM. These requirements include elements of re-usability, interoperability, interchangeability, maintainability, extensibility, and autonomy across the entire DT lifecycle. A baseline framework for DT technology has been developed that addresses many aspects of these requirements and enables the addressing of the requirements more fully through additional specification. The baseline framework includes a definition of a DT and an object-oriented (O-O) architecture for DTs that defines generalization, aggregation and instantiation of DT classes. Case studies using and extending the baseline framework illustrate its advantages in supporting DT solutions and trends in SM.

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“…Future work will benefit from considering larger sample with multiple repetitions of individuals with varying in genders, ages, etc. The proposed framework methodology tends to fulfill the four dimensions of a true DT, as concluded by [86], i.e., connectivity, analyzability, visibility, and granularity. The first component, "Connectivity," deals with the DT being a copy of the real system.…”

Section: Discussionmentioning

confidence: 99%