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Industrial Metaverse Digital Twin: ISO 23247 Compliant Architecture for AI-Driven Simulation

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Detalhes bibliográficos
Resumo:The Industrial Metaverse marks a new stage in Industry 4.0, raising the representation level of Digital Twins (DT) from discrete elements to an interconnected network of assets covering the entire production ecosystem. This paradigm changing reflects advances in enabling technologies such as Artificial Intelligence (AI) and complex what-if simulations. As complexity increases, adopting established industrial standards for implementing DT functionalities becomes imperative to specify guidelines for companies and researchers. This paper proposes a functional architecture for DT implementation in compliance with ISO 23247 standard, aiming to support the development of interoperable and standardized solutions combined within the Industrial Metaverse. The architecture was employed to develop a DT framework for an automotive assembly line, covering the quality inspection process and embedding AI-based mechanisms to leverage the what-if simulation of deviations in structural parameters of the vehicle's body. Experimental results demonstrate the tool's ability to accurately predict outputs for critical quality parameters according to hypothetical measurement scenarios, leveraging the production stakeholders' understanding regarding the correlated impact of deviations at different structural points, and demonstrating the versatility and potential of combining AI strategies for what-if simulations.
Autores principais:Oliveira Júnior, Alexandre de
Outros Autores:Calvo-Rolle, José Luis; Pires, Rui; Leitão, Paulo
Assunto:Industrial metaverse Artificial intelligence What-if Simulation Digital twin ISO 23247 Zero defect manufacturing
Ano:2025
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Bragança
Idioma:inglês
Origem:Biblioteca Digital do IPB
Descrição
Resumo:The Industrial Metaverse marks a new stage in Industry 4.0, raising the representation level of Digital Twins (DT) from discrete elements to an interconnected network of assets covering the entire production ecosystem. This paradigm changing reflects advances in enabling technologies such as Artificial Intelligence (AI) and complex what-if simulations. As complexity increases, adopting established industrial standards for implementing DT functionalities becomes imperative to specify guidelines for companies and researchers. This paper proposes a functional architecture for DT implementation in compliance with ISO 23247 standard, aiming to support the development of interoperable and standardized solutions combined within the Industrial Metaverse. The architecture was employed to develop a DT framework for an automotive assembly line, covering the quality inspection process and embedding AI-based mechanisms to leverage the what-if simulation of deviations in structural parameters of the vehicle's body. Experimental results demonstrate the tool's ability to accurately predict outputs for critical quality parameters according to hypothetical measurement scenarios, leveraging the production stakeholders' understanding regarding the correlated impact of deviations at different structural points, and demonstrating the versatility and potential of combining AI strategies for what-if simulations.