Integration challenges for digital twin systems-of-systems

Michael, Judith; Pfeiffer, Jérôme; Rumpe, Bernhard; Wortmann, Andreas

doi:10.1145/3528229.3529384

Cited by 32 publications

(13 citation statements)

References 19 publications

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“…At a third development level, DTs are connected and shared across different actors and organizations. The simulation models underlying these IDTs become more meaningful when DTs of different actors are combined, but also when discrete or composite DTs are utilized by different actors from different perspectives (Michael et al, 2022; Redeker et al, 2021; Silva et al, 2022). IDTs enable the usage and commercialization of vast amounts of heterogeneous data across organizations in all stages of a product's life cycle from development and production to usage, service, and recycling.…”

Section: Technical and Theoretical Backgroundmentioning

confidence: 99%

“…The rise of IDTs creates challenges in traditional business‐to‐business relationships in vertically integrated, rigid supply chains characterized by asset‐specific and process‐specific investments, as typical for industrial manufacturing firms today (Fuller et al, 2020; Michael et al, 2022). IDTs establish a different logic of value creation and innovation by connecting multiple sides of the market, including competing actors.…”

Section: Technical and Theoretical Backgroundmentioning

confidence: 99%

“…However, research lacks implication on how IDTs impact the amount and quality of external knowledge inflows into the innovation process while governing the resulting openness (Michael et al, 2022; West et al, 2021). IDTs build on the idea of open data exchange between all connected entities following a platform logic (Gawer, 2014; Xu et al, 2020) to create value and drive innovation jointly (Redeker et al, 2021; Silva et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…Such a decision is challenging for most established firms and causes an inherent tradeoff between data openness and knowledge protection (e.g., Laursen & Salter, 2014; Moschko et al, 2023; Parker & van Alstyne, 2018; Stanko et al, 2017). Hence, exchanging data through IDTs among different actors poses new challenges and uncertainties (Fuller et al, 2020; Michael et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

“…Companies also face uncertainties about the effects of IDTs on their business model, or how IDTs can become drivers for business model innovation (Stark, 2022; Xu et al, 2020). So far, it is uncertain how IDTs can overcome some of the limitations that humans face in innovation management, such as information searching, processing, and evaluation enabling data‐driven decision‐making while collaborating and cocreating across different domains and external stakeholders (Michael et al, 2022; West et al, 2021). With our study, we aim to contribute to a better understanding of how IDTs impact future digital manufacturing and innovation.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Interconnected digital twins and the future of digital manufacturing: Insights from a Delphi study

Dyck

Lüttgens

Piller

et al. 2023

J of Product Innov Manag

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Digital twins (DTs) are virtual representations of real-world entities like production assets, processes, or products. They are updated at a defined fidelity and frequency along the entire life cycle from development and engineering over the production or implementation of a product or process until its usage stage. Interconnected digital twins (IDTs) are DTs shared and connected across organizations with the objective to create holistic simulation and decision models of an entire physical system. In this paper, we investigate how IDTs shape future digital manufacturing scenarios and impact innovation management. We present the results of a real-time Delphi study, analyzing quantitative and qualitative estimates on a set of 24 projections, forecasting the future of digital manufacturing with a projection horizon towards 2030. Using this data and 22 additional use cases of IDTs in manufacturing companies, we present a baseline scenario where our Delphi panel reached a consensus, representing a likely future of digital manufacturing in 2030. By analyzing projections where our expert panels' evaluations vary widely, we identify key design decisions that may impact innovation management along the dimensions of variation, choice, and control in digital manufacturing. We explain how IDTs will impact external knowledge inflows, the emergence and governance of industrial data spaces, and the potential of data-driven and AI-enabled applications for prediction and regulation to drive better decisionmaking and continuous innovation.

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Section: Technical and Theoretical Backgroundmentioning

confidence: 99%

Section: Technical and Theoretical Backgroundmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Interconnected digital twins and the future of digital manufacturing: Insights from a Delphi study

Dyck

Lüttgens

Piller

et al. 2023

J of Product Innov Manag

View full text Add to dashboard Cite

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Model‐based digital twins of medicine dispensers for healthcare IoT applications

Sartaj,

Ali,

Yue

et al. 2024

Softw Pract Exp

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SummaryHealthcare applications with the Internet of Things (IoT) are often safety‐critical, thus, require extensive testing. Such applications are often connected to smart medical devices from various vendors. System‐level testing of such applications requires test infrastructures physically integrating medical devices, which is time and monetary‐wise expensive. Moreover, applications continuously evolve, for example, introducing new devices and users and updating software. Nevertheless, a test infrastructure enabling testing with a few devices is insufficient for testing healthcare IoT systems, hence compromising their dependability. In this paper, we propose a model‐based approach for the creation and operation of digital twins (DTs) of medicine dispensers as a replacement for physical devices to support the automated testing of IoT applications at scale. We evaluate our approach with an industrial IoT system with medicine dispensers in the context of Oslo City and its industrial partners, providing healthcare services to its residents. We study the fidelity of DTs in terms of their functional similarities with their physical counterparts: medicine dispensers. Results show that the DTs behave more than 92% similar to the physical medicine dispensers, providing a faithful replacement for the dispenser.

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