Work

Towards a collaborative approach for Digital Twin simulation models comprehension

Year: 2024

Type: conference-paper

Abstract: Digital twins (DTs) are highly accurate virtual replicas of physical objects that enhance functionality through simulation, prediction, and analysis capabilities. Constructing DT can be considered a collaborative process between experts who need to integrate different simulation models to create cohesive services. However, challenges arise in comprehending the functionalities of these models, understanding how to use and reuse them, and effectively transferring knowledge for collaborative purposes. This paper lays the foundation for a collaborative model-based approach to addressing these challenges and enhancing comprehension of simulation models and knowledge sharing. This is achieved through a metamodel that represents the knowledge base and a detailed procedure designed to enhance model knowledge assimilation and sharing within a collaborative process.

Source: ACM/IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS)

DOI: 10.1145/3652620.3688559

Authors: Arianna Fedeli, David Azael Manrique Negrin

Institutions: Gran Sasso Science Institute, Eindhoven University of Technology

Language: English

Topic: Digital Transformation in Industry

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Funder: Nederlandse Organisatie voor Wetenschappelijk Onderzoek

Awards: G1502848176, G5522762047