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- W4379983503 abstract "Virtualization is one key design principle in Industry 4.0, with the modeling and simulation of the physical assets playing crucial roles in the Digital Twin context. Different approaches can be used to implement the virtual asset models, ranging from simple equations to complex mathematical models. Petri nets formalism is a suitable approach to model and simulate the physical asset operation in the Digital context, particularly those that are event-driven, taking advantage of its inherent robust mathematical foundation. Having this in mind, this paper proposes a Petri nets approach, which considers Artificial Intelligent data-driven analytics associated to timed transitions to support the execution of what-if simulation aiming the monitoring, diagnosis, prediction, and optimization. The proposed approach was tested in an experimental punching machine, allowing the early identification the performance degradation in the Digital Twin and the selection of actions to be implemented in the physical asset to improve its operation." @default.
- W4379983503 created "2023-06-10" @default.
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- W4379983503 date "2023-04-04" @default.
- W4379983503 modified "2023-10-16" @default.
- W4379983503 title "Artificial Intelligence Data-Driven Petri nets Approach for Virtualizing Digital Twins" @default.
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- W4379983503 doi "https://doi.org/10.1109/icit58465.2023.10143087" @default.
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