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 International Conference on Advanced Information Systems Engineering 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
International Conference on Advanced Information Systems Engineering
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 International Conference on Advanced Information Systems Engineering tenutosi a Zaragoza, Spain) [10.1007/978-3-031-34674-3_14].
File allegati a questo prodotto
File Dimensione Formato  
DeGiacomo_AIDA_2023.pdf.pdf

accesso aperto

Note: https://link.springer.com/chapter/10.1007/978-3-031-34674-3_14
Tipologia: Documento in Pre-print (manoscritto inviato all'editore, precedente alla peer review)
Licenza: Creative commons
Dimensione 415.84 kB
Formato Adobe PDF
415.84 kB Adobe PDF
DeGiacomo_AIDA_2023.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 7.83 MB
Formato Adobe PDF
7.83 MB Adobe PDF   Contatta l'autore

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1682754
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 4
  • ???jsp.display-item.citation.isi??? 2
social impact