Solimando, Michele
(2022)
A distributed middleware for IT/OT convergence in modern industrial environments, [Dissertation thesis], Alma Mater Studiorum Università di Bologna.
Dottorato di ricerca in
Computer science and engineering, 34 Ciclo. DOI 10.48676/unibo/amsdottorato/10074.
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Abstract
The modern industrial environment is populated by a myriad of intelligent devices that collaborate for the accomplishment of the numerous business processes in place at the production sites. The close collaboration between humans and work machines poses new interesting challenges that industry must overcome in order to implement the new digital policies demanded by the industrial transition.
The Industry 5.0 movement is a companion revolution of the previous Industry 4.0, and it relies on three characteristics that any industrial sector should have and pursue: human centrality, resilience, and sustainability. The application of the fifth industrial revolution cannot be completed without moving from the implementation of Industry 4.0-enabled platforms. The common feature found in the development of this kind of platform is the need to integrate the Information and Operational layers. Our thesis work focuses on the implementation of a platform addressing all the digitization features foreseen by the fourth industrial revolution, making the IT/OT convergence inside production plants an improvement and not a risk. Furthermore, we added modular features to our platform enabling the Industry 5.0 vision. We favored the human centrality using the mobile crowdsensing techniques and the reliability and sustainability using pluggable cloud computing services, combined with data coming from the crowd support.
We achieved important and encouraging results in all the domains in which we conducted our experiments. Our IT/OT convergence-enabled platform exhibits the right performance needed to satisfy the strict requirements of production sites. The multi-layer capability of the framework enables the exploitation of data not strictly coming from work machines, allowing a more strict interaction between the company, its employees, and customers.
Abstract
The modern industrial environment is populated by a myriad of intelligent devices that collaborate for the accomplishment of the numerous business processes in place at the production sites. The close collaboration between humans and work machines poses new interesting challenges that industry must overcome in order to implement the new digital policies demanded by the industrial transition.
The Industry 5.0 movement is a companion revolution of the previous Industry 4.0, and it relies on three characteristics that any industrial sector should have and pursue: human centrality, resilience, and sustainability. The application of the fifth industrial revolution cannot be completed without moving from the implementation of Industry 4.0-enabled platforms. The common feature found in the development of this kind of platform is the need to integrate the Information and Operational layers. Our thesis work focuses on the implementation of a platform addressing all the digitization features foreseen by the fourth industrial revolution, making the IT/OT convergence inside production plants an improvement and not a risk. Furthermore, we added modular features to our platform enabling the Industry 5.0 vision. We favored the human centrality using the mobile crowdsensing techniques and the reliability and sustainability using pluggable cloud computing services, combined with data coming from the crowd support.
We achieved important and encouraging results in all the domains in which we conducted our experiments. Our IT/OT convergence-enabled platform exhibits the right performance needed to satisfy the strict requirements of production sites. The multi-layer capability of the framework enables the exploitation of data not strictly coming from work machines, allowing a more strict interaction between the company, its employees, and customers.
Tipologia del documento
Tesi di dottorato
Autore
Solimando, Michele
Supervisore
Dottorato di ricerca
Ciclo
34
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Industry 5.0, Industry 4.0, IT/OT Convergence, Industrial IoT, Cyber-physical systems, Crowdsensing, Cloud Computing, Edge Computing, Cybersecurity.
URN:NBN
DOI
10.48676/unibo/amsdottorato/10074
Data di discussione
23 Giugno 2022
URI
Altri metadati
Tipologia del documento
Tesi di dottorato
Autore
Solimando, Michele
Supervisore
Dottorato di ricerca
Ciclo
34
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
Industry 5.0, Industry 4.0, IT/OT Convergence, Industrial IoT, Cyber-physical systems, Crowdsensing, Cloud Computing, Edge Computing, Cybersecurity.
URN:NBN
DOI
10.48676/unibo/amsdottorato/10074
Data di discussione
23 Giugno 2022
URI
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