Digital Twin

Connections to other Concepts

May contain a Digital Shadow
Contains Digital Master
There are various forms of representations, either singular or in conjunction, like Asset Administration Shell, Digital Product Passport and Digital Nameplate
Can aggregate different other representations of the physical item, like BIM

To date, there is no consensus on what a digital twin is and what characteristics it should have. Many different definitions and characteristics have emerged.
Nevertheless, the description of the digital twin has been developing steadily since 2003 and has decoupled itself from the NASA definition as a pure simulation of a system.
Current definition: A digital twin is a digital representation of a product instance (real device, object, machine, service or intangible good) or an instance of a product-service system (a system consisting of product and associated service).
A digital twin contains selected characteristics, states and behaviour of the product instance or system
Allows simulation, control and improvement of the systems
According to the different levels of integration, the digital twin can be divided into three subcategories: Digital Model (DM), Digital Shadow (DS) and Digital Twin (DT)
Can be based on the Digital Master and linked to the Digital Shadow.

A digital twin is a digital representation of an instance
A digital twin can be in multiple locations simultaneously
A digital twin has multiple states
In an interaction situation, the digital twin has a context-specific state
The information model for digital twins is infinite, it is a real information model
The real information model can be finitely approximated for a specific application scenario and thus becomes a rational information model
The rational information model cannot be stored in one place
The rational information model is never completely visible

2002: The concept of the digital twin goes back to a presentation by Dr. Michael Grieves at the University of Michigan on the foundation of a Product Lifecycle Management (PLM) centre.
The presentation was called "Conceptual Ideal for PLM" and contained various elements of the Digital Twin: real model, virtual model, the connection of the data flow from the real to the virtual model...
2010: A first definition of the term "Digital Twin" was published by the National Aeronautics and Space Administration (NASA):
- "integrated multiphysics, multilevel, probabilistic simulation of a vehicle or system that uses the best available physical models, sensor updates, fleet history, etc., to represent the life of its "flying twin". Following this definition, the Digital Twin is a highly detailed simulation model of spacecraft or aircraft that attempts to reproduce physical behaviour as accurately as possible in the virtual world."

Production monitoring, production optimisation, predictive maintenance, quality management, restructuring, plant planning and virtual commissioning, logistics planning Product monitoring, product development
Diagnosis and prognosis of real product instance behaviour as well as safeguarding of new product generations
Basis for the development of new business models

The digital shadow is the process data that machines generate during their operation when producing an instance.
This is raw data, which is also referred to as a digital footprint.
These include, for example, operating and status data, process data, layout data, scan data...
Is enriched with real data from the use of the real product

On the one hand, data is the input for condition monitoring and on the other hand, it forms the basis for comprehensive insights that can be gained through data mining (pattern finding in the raw data)
Allows conclusions to be drawn from the enriched data, as well as optimizations and changes to be tested and made

https://www.industrie40.net/index.php/61-beitraege-d/224-digitaler-schatten

Enables organisations to collect and maintain system information and to make system information available to stakeholders at a given point in time.
Represents a document-based approach in the development of complex products that enables modern organisations to exchange product data with downstream processes

Allows conclusions to be drawn from the enriched data, and optimisations and changes to be tested and implemented