A digital twin is a virtual representation of a physical entity or system. A digital twin is much more than a picture, blueprint or schematic: It is a dynamic, simulated view of a physical product that is continuously updated throughout the design, build and operation lifecycle, and exists in parallel to its corresponding physical object. Digital twins can provide customer and equipment insights, improve quality and reliability, monitor performance, and mitigate downtime and increase availability. This session looks at the potential of digital twins to drive innovation, ways to introducing digital twinning as a way-of-working in the high tech industry, and its impact on an R&D organization.

Moderation: Teun Hendriks, ESI (TNO)

CHAIR: Hans Duetz, Philips IGT

How can digital twinning drive design and engineering innovation?

The presentation starts with defining Digital Twinning. Then, the perspective of Philips Image Guided Therapy Systems on the potential of Digital Twinning will be presented. Philips leads the market of Image Guided Therapy Systems for minimally-invasive patient interventions. Current trends demand more tailored and integrated solutions and better user experience. In this context Philips Image Guided Therapy Systems runs several initiatives to explore Digital Twinning, with the Virtual Cathlab as a prime example.

Jacques Verriet, ESI

From virtual prototype to digital twin

In traditional model-driven development, models are used to guide system development. Models are used to analyze aspects of the system under development and identify the appropriate trade-off between different system qualities. To analyze a system’s behavior, simulation models are used; these virtual prototypes allow analysis and optimization of system behavior under realistic usage scenarios.

The simulation models do not lose their value when the system has become operational. Then they can be used as digital twins to analyze the system’s performance. The simulation models can be used as a reference to identify anomalous or suboptimal system behavior.

We will demonstrate ESI’s work on virtual prototyping and digital twin using an example from the smart lighting domain. A simulation models is used to iteratively specify and analyze the behavior of an office building. The final specification is used as a basis for anomaly detection of the operational lighting system: differences of the digital and physical twin are automatically detected, and their underlying causes are analyzed using a rule-based approach.

Currently, human intervention is needed to correct the system’s anomalies by taking away the root cause. For the future, we expect a large part of this to be done by the system itself. This will be illustrated using a vision on how digital twins can support the development of autonomous adaptive systems.

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Louis Stroucken, Philips Innovation Services

Model-Based Systems Engineering and Digital Twins: applications to design, manufacturing and service of systems

High-tech and healthcare system are challenging to design, manufacture and service efficiently and effectively. These challenges are well-known in the industry, but we tend to address them as separate, disconnected issues.

In this presentation we will make the case that combining techniques that are usually confined to one of these life cycle phases will yield better results when integrated. We discuss three real-life examples to see how the combination of model-based design and data analysis supports the creation of digital twins and thus achieve breakthrough results.

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