One of the salient features of Industry 4.0 is that machines and other actors involved in the manufacturing process provide Industrial APIs that allow to inquire their status. In order to provide resilience, the manufacturing process should be able to automatically adapt to new conditions, considering new actors for the fulfillment of the manufacturing goals. As a single manufacturing process may include several of these actors, and their interfaces are often complex, this task cannot be easily accomplished in a completely manual way. In this work, we focus on the orchestration of Industrial APIs using Markov Decision Processes (MDPs). We present a tool implementing stochastic composition of processes and we demonstrate it in an Industry 4.0 scenario.

AIDA: A Tool for Resiliency in Smart Manufacturing / DE GIACOMO, Giuseppe; Favorito, Marco; Leotta, Francesco; Mecella, Massimo; Monti, Flavia; Silo, Luciana. - 477:(2023), pp. 112-120. (Intervento presentato al convegno 35th International Conference on Advanced Information Systems Engineering, CAiSE'23 tenutosi a Zaragoza, Spain) [10.1007/978-3-031-34674-3_14].

AIDA: A Tool for Resiliency in Smart Manufacturing

Giuseppe De Giacomo;Marco Favorito;Francesco Leotta;Massimo Mecella;Flavia Monti
;
Luciana Silo
2023

Abstract

One of the salient features of Industry 4.0 is that machines and other actors involved in the manufacturing process provide Industrial APIs that allow to inquire their status. In order to provide resilience, the manufacturing process should be able to automatically adapt to new conditions, considering new actors for the fulfillment of the manufacturing goals. As a single manufacturing process may include several of these actors, and their interfaces are often complex, this task cannot be easily accomplished in a completely manual way. In this work, we focus on the orchestration of Industrial APIs using Markov Decision Processes (MDPs). We present a tool implementing stochastic composition of processes and we demonstrate it in an Industry 4.0 scenario.
2023
35th International Conference on Advanced Information Systems Engineering, CAiSE'23
industrial api; smart manufacturing; service composition
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
AIDA: A Tool for Resiliency in Smart Manufacturing / DE GIACOMO, Giuseppe; Favorito, Marco; Leotta, Francesco; Mecella, Massimo; Monti, Flavia; Silo, Luciana. - 477:(2023), pp. 112-120. (Intervento presentato al convegno 35th International Conference on Advanced Information Systems Engineering, CAiSE'23 tenutosi a Zaragoza, Spain) [10.1007/978-3-031-34674-3_14].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1682754
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