JARVIS is a Research & Development project, jointly developed by industrial SME partners and by the University of Florence, aimed at development of a hardware/software framework supporting integration among physical IoT devices, data analytic software agents, and human operators involved in operation and maintenance of resilient Industry 4.0 systems. At the heart of the JARVIS architecture, a suite of software digital twins deployed in a Java EE environment supports runtime monitoring and control of the hierarchy of hardware configuration items of the system, capturing their composition and representing their failure modes through a reflection architectural pattern enabling agile adaptation to the evolution of configurations. Besides, analytic modules can be deployed as micro-services leveraging both the knowledge base provided by digital twins and the data flowing from the ingestion layer. This enables agile development of advanced monitoring and control services supporting maintainability and resilience. We describe the JARVIS architecture, outlining responsibilities and collaborations among its modules, and we provide details on the structure of representation of digital twins, showing how this is exploited in a data analytic agent providing an executable representation of fault trees associated with failure modes of configuration items.
JARVIS, A Hardware/Software Framework for Resilient Industry 4.0 Systems / Parri, Jacopo; Patara, Fulvio; Sampietro, Samuele; Vicario, Enrico. - STAMPA. - 11732:(2019), pp. 85-93. (Intervento presentato al convegno 11th International Workshop SERENE 2019 - European Dependable Computing Conference (EDCC) tenutosi a Napoli nel 17/09/2019) [10.1007/978-3-030-30856-8_6].
JARVIS, A Hardware/Software Framework for Resilient Industry 4.0 Systems
PARRI, JACOPO;Patara, Fulvio;SAMPIETRO, SAMUELE;Vicario, Enrico
2019
Abstract
JARVIS is a Research & Development project, jointly developed by industrial SME partners and by the University of Florence, aimed at development of a hardware/software framework supporting integration among physical IoT devices, data analytic software agents, and human operators involved in operation and maintenance of resilient Industry 4.0 systems. At the heart of the JARVIS architecture, a suite of software digital twins deployed in a Java EE environment supports runtime monitoring and control of the hierarchy of hardware configuration items of the system, capturing their composition and representing their failure modes through a reflection architectural pattern enabling agile adaptation to the evolution of configurations. Besides, analytic modules can be deployed as micro-services leveraging both the knowledge base provided by digital twins and the data flowing from the ingestion layer. This enables agile development of advanced monitoring and control services supporting maintainability and resilience. We describe the JARVIS architecture, outlining responsibilities and collaborations among its modules, and we provide details on the structure of representation of digital twins, showing how this is exploited in a data analytic agent providing an executable representation of fault trees associated with failure modes of configuration items.
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