Unified data collect for Digital Twin

Dimitri Renard, Antoine Le Mortellec, Ramla Saddem, David Annebicque,
Bernard Riera

► To cite this version:

Dimitri Renard, Antoine Le Mortellec, Ramla Saddem, David Annebicque, Bernard Riera. Unified data collect for Digital Twin. International forum on Digital Twins Design & Operation (DTD&O), Dec 2023, Paris, France. . [hal-04431896](https://hal.science/hal-04431896v1)

HAL Id: hal-04431896

https://hal.science/hal-04431896v1

Submitted on 6 Feb 2024

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# Unified data collect for Digital Twin

Dimitri RENARD*,*, Antoine LE MORTELLEC*,
Ramla SADDEM**, David ANNEBICQUE** et Bernard RIERA**

Prosyst*, CReSTIC-Université de Reims Champagne Ardenne**

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Prosyst

Master of system automation

**Summary** : Data collection is the pivot between the real world and the virtual world of the digital twin. How to facilitate the deployment and use of data collection for a digital twin at scale? We propose the uDC ecosystem which includes a set of tools and services to unify the collection on assets and easily instantiate them repeatedly in your shop floors. This is fed by industrial use-cases, R&D projects such as MADIT and a survey of scientific literature.

## Digital Twin

### Definitions:

"The Digital Twin concept model [...] contains three main parts: a) **physical products** in Real Space, b) **virtual products** in Virtual Space, and c) **the connections** of data and information that ties the **virtual and real products** together."

M. Grieves, « Digital Twin: Manufacturing Excellence through Virtual Factory Replication », 2014.

"<manufacturing> fit for purpose
**digital representation** of an
**observable manufacturing** element with synchronization
between the element and its
digital representation"

ISO 23247-1:2021,
Digital twin framework for manufacturing, 2021

<figure><img src="image_3.png" /><figcaption>fig 1 : Reference architecture - ISO 23247</figcaption></figure>

### Data collect is a key point in the digital twin architecture (fig 1):

So, to create a digital twin you need :

* Human resources trained and available

* Knowledge of its equipment

* Technical collection capacity for the need

* Consider the use-case for which the digital twin has been designed

→ For large-scale implementation and cost reduction, standardization of digital twin and its data collect becomes necessary

## First Prosyst Digital Twin Application : MADIT

### Railway Machinery Digital Twin Application :

MADIT is a R&D project based on the creating of a digital twin model (fig 2). It has enabled a first approach to this exciting technology.

Prosyst was involved in the data collection and data publication part of the project. Feedback and technological barriers have shown the importance of tools to easily deploy large-scale data collection to meet the needs of digital twins.

<figure><img src="image_4.png" /><figcaption>fig 2 : Machine Digital Twin Project</figcaption></figure>

## Unified data collect for Digital Twin

### Unified Data Collector (uDC):

uDC server and its ecosystem are designed for the deployment of **standardized** and **contextualized** data collection and their associated services (fig 3). It is based on the OPC UA standard IEC 62541. The uDC ecosystem includes self-configurable monitoring services.

uDC ecosystem can be considered as a digital twin because there are :

* A Real Space

* A Bidirectional Communication

* Data and Models

* Services

<figure><img src="image_5.png" /><figcaption>fig 3 : uDC Framework</figcaption></figure>

### Easy deployment of data collect:

Asset modeling allows a standard data structure, presets for variable mapping, information necessary for the connection, etc. (fig 4). Edge computing operations can be integrated into assets.

This makes it **easier to scale up** data collection and use contextualized data via standard services, for example.

Duplicating instances of digital twin facilitates the return on investment of this promising technology.

<figure><img src="image_6.png" /><figcaption>fig 4 : Standard Asset for easily deployment</figcaption></figure>

## Conclusion

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Data Collect is the **basis of the digital twin** for the connection between real and virtual

Unified and contextualized data collection offers **scalability** to develop your digital twins

Digital twin requires large skills to be designed and deployed

## Contact

Dimitri RENARD : drenard@prosyst.fr

Antoine LE MORTELLEC : alemortellec@prosyst.fr

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