Internet of Things (IoT) arises from the convergence between sensors, processing and network communication of specialized digital devices designed to be used wherever it is necessary to collect and process information, automate or integrate the operation of different devices. Compared to embedded systems, of which it collects the legacy, the concept of Internet of Things develops the contents of the network communication at the highest level to allow interaction between objects, such as between production equipment intended to operate together, or between equipment and company systems used for planning, safety and maintenance. This capacity for dialogue now enables to use cloud services (personal storage space accessible at any time and place by simply using an Internet connection) for sophisticated data processing or for the inclusion in complex business processes. In other words, the Internet of Things makes it possible to computerize and to put online "things", exactly as personal computers and smartphones have already done with people. IoT connectivity offers the manufacturing sector an increasing number of ways to access sensor-based data installed in industrial machines and equipment. This results in an increasingly crucial need for information analysis, management and control methods. The amount of data collected by monitoring a smart factory can indeed be enormous, but if not aggregated and organized in such a way as to support the decision-making process, they are unfortunately of any use. One method, which is imposing itself as an invaluable one for those design and customer service teams, which aim to exploit the data collected as well as possible, is that of the Digital Twin. Consequently, we try to describe what the Digital Twin consists of and what are its main applications. Finally, we will focus on 3 particular case-studies regarding its use in the manufacturing field.
Internet of Things (IoT), nella definizione italiana “Internet delle cose”, nasce dalla convergenza tra sensoristica, elaborazione e comunicazione in rete di apparati digitali specializzati pensati per essere impiegati ovunque serva raccogliere ed elaborare informazioni, automatizzare o integrare il funzionamento di dispositivi diversi. Rispetto ai sistemi embedded, di cui raccoglie il testimone, il significato di Internet of Things sviluppa al massimo livello i concetti della comunicazione in rete per permettere l’interazione tra oggetti, come ad esempio tra apparati di produzione destinati a operare insieme, tra apparati e sistemi aziendali utilizzati per la pianificazione, la sicurezza e la manutenzione. Tale capacità di dialogo consente oggi di avvalersi dei servizi in cloud (spazio di archiviazione personale che risulta essere accessibile in qualsiasi momento ed in ogni luogo utilizzando semplicemente una qualunque connessione ad Internet) per elaborazioni dati sofisticate o per l’inserimento in processi di business complessi. In parole povere dunque l’Internet of Things permette di informatizzare e mettere in rete le “cose”, esattamente come personal computer e smartphone hanno fatto con le persone. La connettività IoT offre al settore manifatturiero un numero crescente di modi per accedere ai dati basati su sensori installati in macchine e apparecchiature industriali, e da questo deriva una necessità sempre più cruciale di metodi di analisi, gestione e controllo delle informazioni. La quantità di dati raccolti dal monitoraggio di una smart factory può essere infatti enorme, ma se quest’ultimi non vengono aggregati ed organizzati in modo tale da supportare il processo decisionale, non sono purtroppo di alcuna utilità. Un metodo che si sta rivelando inestimabile per i team di progettazione e assistenza clienti che cercano di sfruttare al meglio i dati raccolti è quello del Digital Twin. In questo elaborato si cercherà dunque di descrivere in cosa consiste il Digital Twin e quali sono le sue principali applicazioni. Ci soffermeremo infine su 3 particolari casi di studio riguardanti il suo utilizzo in campo manifatturiero.
Analisi degli strumenti per la realizzazione dei Digital Twin per scopi industriali
BREGA, SIMONE
2019/2020
Abstract
Internet of Things (IoT) arises from the convergence between sensors, processing and network communication of specialized digital devices designed to be used wherever it is necessary to collect and process information, automate or integrate the operation of different devices. Compared to embedded systems, of which it collects the legacy, the concept of Internet of Things develops the contents of the network communication at the highest level to allow interaction between objects, such as between production equipment intended to operate together, or between equipment and company systems used for planning, safety and maintenance. This capacity for dialogue now enables to use cloud services (personal storage space accessible at any time and place by simply using an Internet connection) for sophisticated data processing or for the inclusion in complex business processes. In other words, the Internet of Things makes it possible to computerize and to put online "things", exactly as personal computers and smartphones have already done with people. IoT connectivity offers the manufacturing sector an increasing number of ways to access sensor-based data installed in industrial machines and equipment. This results in an increasingly crucial need for information analysis, management and control methods. The amount of data collected by monitoring a smart factory can indeed be enormous, but if not aggregated and organized in such a way as to support the decision-making process, they are unfortunately of any use. One method, which is imposing itself as an invaluable one for those design and customer service teams, which aim to exploit the data collected as well as possible, is that of the Digital Twin. Consequently, we try to describe what the Digital Twin consists of and what are its main applications. Finally, we will focus on 3 particular case-studies regarding its use in the manufacturing field.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12075/2775