A Conceptual Model for Digital Shadows in Industry and Its Application

Becker, Fabian; Bibow, Pascal; Dalibor, Manuela; Gannouni, Aymen; Hahn, Viviane; Hopmann, Christian; Jarke, Matthias; Koren, István; Kröger, Moritz; Lipp, Johannes; Maibaum, Judith; Michael, Judith; Rumpe, Bernhard; Sapel, Patrick; Schäfer, Niklas; Schmitz, Georg J.; Schuh, Günther; Wortmann, Andreas

doi:10.1007/978-3-030-89022-3_22

Cited by 54 publications

(23 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We have already proposed a conceptual model [10] to describe digital shadows and demonstrate it using a concrete example. The conceptual model was established through interdisciplinary research and intensive discussions and was evaluated in various real-world manufacturing scenarios.…”

Section: Digital Twins Vs Digital Shadowmentioning

confidence: 99%

“…Figure 3 shows the components of Digital Shadows: models, data, and metadata. We refer the reader to our work [10] for details on the conceptual model of Digital Shadows. Digital Shadows refine other Digital Shadows by providing more detailed models, by adding up-to-date data, by deriving new Digital Shadows using AI methods, or by combining the information contained in other Digital Shadows into a new Digital Shadow.…”

Section: Digital Shadows Enable the Internet Of Productionmentioning

confidence: 99%

“…Example. Domain experts from e-vehicle production define one or more Digital Shadow Types [22] based on a conceptual model [10] for purposes related to production, e.g., quality monitoring or predictive maintenance. These types can be used as blueprints for concrete Digital Shadows recorded from production data at runtime, e.g., a Digital Shadow Type might serve the purpose to minimize the product rejection rate of the grinding process of front window panes and capture the related information accordingly.…”

Section: Model-driven Digital Shadowsmentioning

confidence: 99%

See 2 more Smart Citations

A Computer Science Perspective on Digital Transformation in Production

Brauner

Dalibor

Jarke

et al. 2022

ACM Trans. Internet Things

Self Cite

View full text Add to dashboard Cite

The Industrial Internet-of-Things (IIoT) promises significant improvements for the manufacturing industry by facilitating the integration of manufacturing systems by Digital Twins. However, ecological and economic demands also require a cross-domain linkage of multiple scientific perspectives from material sciences, engineering, operations, business, and ergonomics, as optimization opportunities can be derived from any of these perspectives. To extend the IIoT to a true Internet of Production , two concepts are required: first, a complex, interrelated network of Digital Shadows which combine domain-specific models with data-driven AI methods; and second, the integration of a large number of research labs, engineering, and production sites as a World Wide Lab which offers controlled exchange of selected, innovation-relevant data even across company boundaries. In this article, we define the underlying Computer Science challenges implied by these novel concepts in four layers: Smart human interfaces provide access to information that has been generated by model-integrated AI . Given the large variety of manufacturing data, new data modeling techniques should enable efficient management of Digital Shadows, which is supported by an interconnected infrastructure . Based on a detailed analysis of these challenges, we derive a systematized research roadmap to make the vision of the Internet of Production a reality.

show abstract

Section: Digital Twins Vs Digital Shadowmentioning

confidence: 99%

Section: Digital Shadows Enable the Internet Of Productionmentioning

confidence: 99%

Section: Model-driven Digital Shadowsmentioning

confidence: 99%

See 1 more Smart Citation

A Computer Science Perspective on Digital Transformation in Production

Brauner

Dalibor

Jarke

et al. 2022

ACM Trans. Internet Things

Self Cite

View full text Add to dashboard Cite

show abstract

“…An example is the (optimal) scheduling for production orders on the shopfloor. Due to different optimization objectives, for example, minimization of adherence to due dates or maximization of machines utilization, different schedules that are optimal regarding their optimization objective can be calculated 5,6 . The Digital Shadow provides the decision‐makers with all optimal solutions to decide which option should be realized.…”

Section: Comparison Of Digital Twins and Digital Shadowsmentioning

confidence: 99%

Challenges and research agenda for realizing a seamless integration of Digital Shadows into the production domain

Sapel

Hopmann

2022

Engineering Reports

Self Cite

View full text Add to dashboard Cite

One vision of industry 4.0 is an autonomous shopfloor configuration. A possibility to transfer this vision to reality is realizable with Digital Shadows. As Digital Shadows are well defined in research, challenges for seamless integration in production are still an open research topic. The main challenge is the enrichment of semantics on the domain in a standardized format that enables multilateral communication between all assets. To overcome these challenge, tools have to be developed to support domain experts in building and integrating Digital Shadows without knowledge of modeling and programming. This article demonstrates the main challenges of this objective and proposes a research agenda to close this research gap.

show abstract

“…While recent advances concerning CPS and the IIoT contribute to promising developments with an application in production [4], [10], [11], [14]- [16], [19], [21]- [23], [25], [31], [41], [45], [46], [52], [62], [65], [68], [70]- [72], [76], [77], [81], [83], [97]- [99], [108], [109], the need for security to enable novel forms of industrial collaboration must be especially considered for real-world deployments, where CPS are likely connected to the Internet. Apart from operational reasons (e.g., to ensure safety or privacy), secure approaches also convince traditionally conservative stakeholders, such as companies that fear for their competitiveness, to contribute to cross-domain and inter-company collaborations.…”

Section: A Towards An Internet Of Productionmentioning

confidence: 99%

Collaboration is not Evil: A Systematic Look at Security Research for Industrial Use

Pennekamp¹,

Buchholz²,

Dahlmanns³

et al. 2020

Proceedings 2020 Learning From Authoritative Security Experiment Results Workshop

View full text Add to dashboard Cite

Following the recent Internet of Things-induced trends on digitization in general, industrial applications will further evolve as well. With a focus on the domains of manufacturing and production, the Internet of Production pursues the vision of a digitized, globally interconnected, yet secure environment by establishing a distributed knowledge base. Background. As part of our collaborative research of advancing the scope of industrial applications through cybersecurity and privacy, we identified a set of common challenges and pitfalls that surface in such applied interdisciplinary collaborations. Aim. Our goal with this paper is to support researchers in the emerging field of cybersecurity in industrial settings by formalizing our experiences as reference for other research efforts, in industry and academia alike. Method. Based on our experience, we derived a process cycle of performing such interdisciplinary research, from the initial idea to the eventual dissemination and paper writing. This presented methodology strives to successfully bootstrap further research and to encourage further work in this emerging area. Results. Apart from our newly proposed process cycle, we report on our experiences and conduct a case study applying this methodology, raising awareness for challenges in cybersecurity research for industrial applications. We further detail the interplay between our process cycle and the data lifecycle in applied research data management. Finally, we augment our discussion with an industrial as well as an academic view on this research area and highlight that both areas still have to overcome significant challenges to sustainably and securely advance industrial applications. Conclusions. With our proposed process cycle for interdisciplinary research in the intersection of cybersecurity and industrial application, we provide a foundation for further research. We look forward to promising research initiatives, projects, and directions that emerge based on our methodological work.

show abstract

A Conceptual Model for Digital Shadows in Industry and Its Application

Cited by 54 publications

References 22 publications

A Computer Science Perspective on Digital Transformation in Production

A Computer Science Perspective on Digital Transformation in Production

Challenges and research agenda for realizing a seamless integration of Digital Shadows into the production domain

Collaboration is not Evil: A Systematic Look at Security Research for Industrial Use

Contact Info

Product

Resources

About