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A structure of modelling depths in behavior models for Digital Twins
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Abstract
Behavior models in the Digital Twin are relevant to many use cases such as digital product development, virtual system optimization or virtual commissioning. However, such behavior models are structured in the literature according to different criteria and levels, which complicates the selection of the correct properties for specific use cases. One criterion that is discussed very differently is the modeling depth of behavior models. This paper presents different approaches to structure behavior models from literature and introduces a new concept with focus on the modeling depth. These levels of modeling depth, as well as the characteristics of the different modeling depths, are then illustrated using a representative industry scenario.
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Vacuum-based handling is used extensively in automated production and is typically realized through vacuum ejectors. In compressed air-based vacuum generation, only a small fraction of the initially invested electrical energy is useable for the vacuum-based handling process. In practice, oversizing of the vacuum generation system is therefore used to compensate for process-related uncertainties, e.g. leakage. To enable a significant reduction of the required energy consumption, this paper proposes a method for the design of vacuum handling systems and the corresponding handling process with regard to gripper-specific sealing and force transmission capabilities for the gripping of curved or edged objects.
The role of a Digital Twin is increasingly discussed within the context of Cyber-Physical Production Systems. Accordingly, various architectures for the realization of Digital Twin use cases are conceptualized. There lacks, however, a clear, encompassing architecture covering necessary components of a Digital Twin to realize various use cases in an intelligent automation system.
In this contribution, the added value of a Digital Twin in an intelligent automation system is highlighted and various existing definitions and architectures of the Digital Twin are discussed. Flowingly, an architecture for a Digital Twin and an architecture for an Intelligent Digital Twin and their required components are proposed, with which use cases such as plug and produce, self-x and predictive maintenance are enabled.
In the opinion of the authors, a Digital Twin requires three main characteristics: synchronization with the real asset, active data acquisition from the real environment and the ability of simulation. In addition to all the characteristics of a Digital Twin, an Intelligent Digital Twin must also include the characteristics of Artificial Intelligence. The Intelligent Digital Twin can be used for the realization of the autonomous Cyber-Physical Production Systems.
In order to realize the proposed architecture for a Digital Twin, several methods, namely the Anchor-Point-Method, a method for heterogeneous data acquisition and data integration as well as an agent-based method for the development of a co-simulation between Digital Twins were implemented and evaluated.
During virtual commissioning, the real control technology is put into operation in advance using a model-based digital twin of the production system. The growing demands on the significance of digital twins result in the need for higher model depths and model scopes of the behavior models used. However, new approaches to enhance the usable computing power in a real-time simulation are required. This paper presents a real-time co-simulation platform for virtual commissioning. The platform includes the integration of powerful technology-specific simulation solutions based on integration interfaces and a real-time co-simulation architecture based on partitioning, parallelization, synchronization and data exchange mechanisms.
Simulation ist eine etablierte Methode bei der Entwicklung von technischen Systemen. Allerdings erfordert sie meist spezielle Kenntnisse sowie zusätzliche Aufwände bei der Erzeugung der Modelle und zur Ausführung der Simulationen. Mit dem Trend der Digitalisierung und der Technologie des „Digitalen Zwillings“ verstärkt sich der Impuls, ihren Einsatz und ihre durchgängige Verwendung in allen Lebenszyklusphasen eines Systems zu ermöglichen. Der vorliegende Beitrag diskutiert die damit mögliche, veränderte Rolle der Simulation und die sich ergebenden Chancen für virtuelle Inbetriebnahme-Modelle und beschreibt entsprechende technologische Aspekte zur Weiterentwicklung der Simulation.
Bei der virtuellen Planung, Auslegung und Inbetriebnahme steigen die Anforderungen an die Aussagekraft Digitaler Zwillinge zur umfassenden Abbildung der Interaktionen zwischen Prozess, Maschine, Steuerungssystem und Bediener. Die Zunahme der Modellkomplexität eines Digitalen Zwillings stellt die Echtzeitsimulation vor neue Herausforderungen. Dieser Beitrag stellt eine Echtzeit-Co-Simulations Plattform für die Virtuelle Inbetriebnahme mit Hilfe eines Digitalen Zwillings vor. Diese umfasst (i) die Integration leistungsfähiger technologiespezifischer Simulationsmodelle durch Ansätze zur Modellintegration und (ii) die Echtzeit-Co-Simulation auf Basis von Separations-, Parallelisierungs-, Synchronisations- und Datenaustauschmechanismen.
In many areas of modern engineering, especially in the field of plant engineering, models have become indispensable. Models are not only used for construction, but also to simulate the system behavior e.g. for the control design or during virtual commissioning (VC). In all applications, it has to be decided how detailed the created models should be. For this, a methodology for selecting the modeling depth can be used, which is based on four different modeling depths. However, if requirements change during the operation of the system, it may be necessary to change the modeling depth during simulation run time. The main purpose of this article is to present an approach which allows the modeling depth to be adjusted in terms of changing conditions during simulation runtime. This approach is illustrated by an example of a material flow system.
There is no abstract but at least a link: https://d-nb.info/957278721/04
Logos Verlag Berlin: https://www.logos-verlag.de/cgi-bin/buch/isbn/300
ISBN 978-3-89722-300-4
Virtual commissioning is used to test control code deployed on Programmable Logical
Controllers. Simulation models of a plant are the basis for simulation approaches covering virtual
commissioning. However, it is often unclear what granularity these simulation models should have and
how standardized levels of detail and particular model types should be defined. The approach presented
herein identifies appropriate levels of detail and model types based on a hierarchical perception of
automated manufacturing plants. The aim of this contribution is to systematize modelling approaches,
especially the automatic generation of manufacturing plants’ models.
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