Industry 4.0 is a concept describing the implementation of Industrial cyber-physical systems in modern industries, also defined “smart industries”. With Industry 4.0 a wide set of technologies is intended: Internet of things, cloud computing, data analytics, distributed control systems, advanced robotics, artificial intelligence. Major barriers for the rapid and widespread adoption of these new technologies in SMEs are represented by the technical background required to operators, the time to learn new methodologies and technologies and the costs. The purpose of this PhD thesis is to describe the role of Systems Engineering in the Industry 4.0, to enable a structured approach for product development when these technologies are required for the applications in scope. The focus of the research is on the cross-domain methodology based on model-driven design applied to distributed applications, increasingly relevant as they are the basis of IoT systems and decentralized control systems. These technologies are well suited also for the flexibility and scalability they offer in case of lean/iterative project management methodologies like Agile, SaFE. The thesis presents an E2E approach consisting of: Requirements elicitation and management, System Architecture design, Software design, Verification and Validation methodologies, KPI definition for analysing technical success of the application. The technologies analysed and deepened in this thesis are industrial multi-agent systems, data analytics leveraging also on Artificial Intelligence and Natural language processing, data presentation and IoT networks, both with standard internet protocols and low level, energy-optimized, communication protocols. For each topic discussed in the thesis, a review of current state of the art, leveraging on recent articles and papers of scientific relevance, and a technical use case developed and validated in laboratory are presented. The technical use cases are all based on requirements coming from Industrial needs, to keep the concreteness for the design and validation process. The domains verified with the technical use cases are: Automation Engineering, Software Engineering and Smart infrastructure engineering. Finally, purpose of this thesis is also to provide ideas and suggest room for improvement or further study for each topic, with the aim to create an entry point for deepening on related issues for researchers in the Software and Automation community.
Industria 4.0 è un concetto che ha l’intento di descrivere l’implementazione dei sistemi ciberfisici nelle industrie moderne, anche chiamate “Industrie Intelligenti”. Con Industria 4.0 si intende un insieme vasto di tecnologie: internet delle cose, computazione tramite sistemi cloud, analisi dati, controllo di sistemi distribuiti, robotica avanzata, intelligenza artificiale. Le principali barriere per un’adozione rapida e diffusa di tali tecnologie nelle piccole medie imprese sono rappresentate dalle competenze tecniche richieste agli operatori, il tempo necessario per imparare nuove metodologie e tecnologie e i costi correlati. Lo scopo di questa tesi di Dottorato è di descrivere il ruolo dell’ingegneria dei sistemi in Industria 4.0, per abilitare un approccio strutturato allo sviluppo di prodotto quando tali tecnologie sono richieste per le applicazioni in scopo. L’attenzione della ricerca è posta su metodologie per l’analisi di domini differenti basate sulla progettazione guidata dai modelli applicata ai sistemi distribuiti, sempre più rilevanti poiché sono la base di sistemi IoT e di controlli decentralizzati. La tesi presenta un approccio completo costituito da: elicitazione e gestione dei requisiti, progettazione dell’architettura di sistema, progettazione software, metodologie di verifica e validazione, definizione di metriche per analizzare il successo tecnico di un’applicazione. Le tecnologie analizzate e approfondite nella tesi sono i sistemi industriali multi-agente, l’analisi dati basata su intelligenza artificiale e analisi del linguaggio naturale, sistemi di presentazione dei dati e reti di dispositivi IoT, sia con protocolli di rete internet standard che con protocolli di comunicazione di basso livello ed energeticamente ottimizzati. Per ogni tema discusso nella tesi sono presentati lo stato dell’arte basandosi su recenti articoli di rilevanza scientifica e uno caso studio tecnico sviluppato e validato nei laboratori dell’Università. I casi studio sono basati su requisiti provenienti dal mondo industriale al fine di mantenere concretezza nel processo di progettazione e validazione. I domini di questi prototipi di validazione sono: Ingegneria dell’Automazione, Ingegneria del Software, Ingegneria delle infrastrutture intelligenti. Infine, scopo della tesi è anche quello di fornire idee e suggerire spazi di miglioramento o di ulteriori studi per ciascun ambito, con il fine di creare un punto di accesso per l’approfondimento su temi correlati rivolto ai ricercatori della comunità software e automazione.
Ingegneria dei sistemi distribuiti per l’orchestrazione delle tecnologie di Industria 4.0 finalizzate a uno sviluppo di prodotto agile
CERVO, ANDREA
2022
Abstract
Industry 4.0 is a concept describing the implementation of Industrial cyber-physical systems in modern industries, also defined “smart industries”. With Industry 4.0 a wide set of technologies is intended: Internet of things, cloud computing, data analytics, distributed control systems, advanced robotics, artificial intelligence. Major barriers for the rapid and widespread adoption of these new technologies in SMEs are represented by the technical background required to operators, the time to learn new methodologies and technologies and the costs. The purpose of this PhD thesis is to describe the role of Systems Engineering in the Industry 4.0, to enable a structured approach for product development when these technologies are required for the applications in scope. The focus of the research is on the cross-domain methodology based on model-driven design applied to distributed applications, increasingly relevant as they are the basis of IoT systems and decentralized control systems. These technologies are well suited also for the flexibility and scalability they offer in case of lean/iterative project management methodologies like Agile, SaFE. The thesis presents an E2E approach consisting of: Requirements elicitation and management, System Architecture design, Software design, Verification and Validation methodologies, KPI definition for analysing technical success of the application. The technologies analysed and deepened in this thesis are industrial multi-agent systems, data analytics leveraging also on Artificial Intelligence and Natural language processing, data presentation and IoT networks, both with standard internet protocols and low level, energy-optimized, communication protocols. For each topic discussed in the thesis, a review of current state of the art, leveraging on recent articles and papers of scientific relevance, and a technical use case developed and validated in laboratory are presented. The technical use cases are all based on requirements coming from Industrial needs, to keep the concreteness for the design and validation process. The domains verified with the technical use cases are: Automation Engineering, Software Engineering and Smart infrastructure engineering. Finally, purpose of this thesis is also to provide ideas and suggest room for improvement or further study for each topic, with the aim to create an entry point for deepening on related issues for researchers in the Software and Automation community.File | Dimensione | Formato | |
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CERVOA_Distributed Systems Engineering to orchestrate new I4.pdf
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https://hdl.handle.net/20.500.14242/79580
URN:NBN:IT:UNIMORE-79580