Today, the digital transformation through the Industry 4.0 paradigm is becoming a valuable resource to address the business needs of manufacturing players in term of agility, efficiency and real-time reactivity. The adoption of smart technologies, as Big Data, Cloud Computing, Internet of Things and Simulation, in manufacturing systems enables individualized solutions, flexibility and cost savings in industrial processes. The digital transformation of the factory takes shape under the term of smart manufacturing. The cyber-physical integration is an important prerequisite to develop a smart production, and it can be achieved through a simulation environment called Digital Twin (DT). The DT is able to simulate in real-time a system in a virtual environment, synchronized to the real one thanks to sensors and actuators. The interaction of the physical and virtual world has led the introduction of a new paradigm of industrial automation, characterized by decentralization mechanisms. The concept of DT is gaining more and more attention in literature, however there are still few applications in manufacturing context. A clear understanding of the concept and of its benefits is necessary to increase the level of acceptance and adoption of the technology by companies, especially among SMEs. The thesis aims to support the dissemination of DT concept in manufacturing, by providing - from one side - a strategic tool that help SMEs’ managers in the understanding of the potentials of DT and in the identification of a tailored DT application – on the other – a framework of Digital Twin Lifecycle to convey a better interpretation and analysis of the theme to the potential investors. Within the application case in cosmetic industry, the strategic tool has been applied and validated, and a digital model for the machine state monitoring was realized through the SFC graphical language in OpenModelica environment. The creation of scalable structure for the digital model allows the reusability of the model to address other purposes and paves the way for many possible improvements.
Oggi, la trasformazione digitale attraverso il paradigma dell'Industria 4.0 sta diventando una risorsa preziosa per rispondere alle esigenze di business dei produttori in termini di agilità, efficienza e reattività. L'adozione di tecnologie intelligenti, come Big Data, Cloud Computing, Internet of Things e Simulation, nei sistemi di produzione consente soluzioni personalizzate, flessibilità e risparmi di costo nei processi industriali. La trasformazione digitale della fabbrica prende forma sotto il termine Smart Manufacturing. L'integrazione cyber-physical è un importante prerequisito per lo sviluppo di una produzione intelligente, e può essere realizzata tramite un ambiente di simulazione chiamato Digital Twin (DT). Il DT è in grado di simulare in tempo reale un sistema in un ambiente virtuale, in sincrono con il sistema reale. L’interazione tra mondo fisico e virtuale ha introdotto un nuovo paradigma di automazione industriale, caratterizzato da meccanismi di decentramento. Il concetto di DT sta guadagnando sempre più attenzione in letteratura, tuttavia sono ancora poche le applicazioni in ambito manifatturiero. Una chiara comprensione del concetto e dei suoi benefici è necessaria per aumentare il livello di accettazione e adozione della tecnologia da parte delle aziende, soprattutto tra le PMI. La tesi mira a sostenere la diffusione del concetto di DT nel settore manifatturiero, fornendo - da un lato - uno strumento strategico che aiuti i manager delle PMI nella comprensione delle potenzialità del DT e nell'identificazione di un'applicazione di DT su misura - dall'altro - un quadro concettuale sul Digital Twin Lifecycle che intende trasmettere una migliore interpretazione e analisi del tema ai potenziali investitori. All'interno del caso applicativo nell'industria cosmetica, lo strumento strategico è stato applicato e validato, ed un modello digitale per il monitoraggio degli stati macchina è stato realizzato attraverso il linguaggio grafico SFC nell’ambiente di simulazione chiamato OpenModelica. La struttura scalabile adottata per realizzare il modello digitale permette di riutilizzare il modello per altri scopi, e apre la strada a possibili miglioramenti.
Assessment of digital twin solutions and benefits in manufacturing : an application case in the cosmetic industry
Peretti, Luca;Marenco, Raffaella
2020/2021
Abstract
Today, the digital transformation through the Industry 4.0 paradigm is becoming a valuable resource to address the business needs of manufacturing players in term of agility, efficiency and real-time reactivity. The adoption of smart technologies, as Big Data, Cloud Computing, Internet of Things and Simulation, in manufacturing systems enables individualized solutions, flexibility and cost savings in industrial processes. The digital transformation of the factory takes shape under the term of smart manufacturing. The cyber-physical integration is an important prerequisite to develop a smart production, and it can be achieved through a simulation environment called Digital Twin (DT). The DT is able to simulate in real-time a system in a virtual environment, synchronized to the real one thanks to sensors and actuators. The interaction of the physical and virtual world has led the introduction of a new paradigm of industrial automation, characterized by decentralization mechanisms. The concept of DT is gaining more and more attention in literature, however there are still few applications in manufacturing context. A clear understanding of the concept and of its benefits is necessary to increase the level of acceptance and adoption of the technology by companies, especially among SMEs. The thesis aims to support the dissemination of DT concept in manufacturing, by providing - from one side - a strategic tool that help SMEs’ managers in the understanding of the potentials of DT and in the identification of a tailored DT application – on the other – a framework of Digital Twin Lifecycle to convey a better interpretation and analysis of the theme to the potential investors. Within the application case in cosmetic industry, the strategic tool has been applied and validated, and a digital model for the machine state monitoring was realized through the SFC graphical language in OpenModelica environment. The creation of scalable structure for the digital model allows the reusability of the model to address other purposes and paves the way for many possible improvements.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/170461