In the recent years the market has changed radically, thanks to technological developments (especially IT) that have made it possible to create a new business model based on highly variable customer needs and the shortening of the product lifecycle. It is with this in mind that the problem of renewing the industry is born, with a new industrial revolution that is bringing and will bring advantages to those who will adapt to it. The starting point was the financing by the Italian government of the development of Industry 4.0, with the creation of a Competence Center at Politecnico di Milano, and other research and industrial centers, that will allow small to medium-sized enterprises (especially in the manufacturing sector) to see the benefits deriving from this new technological-productive innovation. Another important concept we will focus on is Big Data, that is about very large and complex datasets that require different techniques from the traditional ones to capture and analyze data. We will focus in particular on a characteristic of Big Data, the variety, which refers to all structured and non-structured data that can be generated by people or machines. The purpose of this thesis is therefore to show how it is possible to adopt computer engineering solutions to become part of the fourth industrial revolution, however using a limited number of resources and without completely redesigning the enterprise. We will list the currently available software solutions, showing their capabilities and advantages. From this point we will have to choose which tool to use for our project, and we will explain the reasons that led us to make this decision. We will illustrate the current situation of the market and what is necessary nowadays to be competitive, especially focused at the typical Italian companies that often trudge in the face of foreign competition or are still outdated from the technological point of view. We will then show a practical application of real-time analytics techniques, starting from the chosen platform, to a database coming from an existing company, with the aim of obtaining insights on production and efficiency, giving a clear vision to managers. Last, but not least, we will introduce the problem of data integration and quality, showing a possible application of these techniques to our case study.
Il mercato negli ultimi anni è cambiato radicalmente, grazie agli sviluppi tecnologici (specialmente IT) che hanno reso possibile la creazione di un nuovo modello di business basato sui bisogni dei clienti, altamente variabili, e sull'introduzione di nuovi prodotti in tempi molto più brevi. È in quest'ottica che nasce il problema di rinnovare l'industria, con una nuova rivoluzione industriale che sta portando e porterà vantaggi a chi si adeguerà ad essa. Il punto di partenza è stato il finanziamento da parte del governo italiano allo sviluppo dell'industria 4.0, con la creazione presso il Politecnico di Milano ed altre realtà industriali e di ricerca, di Competence Center che permetteranno alle piccole e medie imprese (soprattutto del settore manufatturiero) di vedere i benefici derivanti da questa nuova innovazione tecnologico-produttiva. Un altro importante concetto sui cui andremo a focalizzarci è quello dei Big Data, dei dataset molto grandi e complessi, che richiedono tecniche differenti da quelle tradizionali per la cattura e l'analisi. Ci concentreremo in particolare su una caratteristica dei Big Data, la variety, la quale si riferisce a tutti i dati strutturati e non, che possono essere generati da persone o da macchine. Lo scopo della tesi è quindi mostrare alcune soluzioni informatiche che permettono di analizzare questi dati ed entrare a far parte della quarta rivoluzione industriale, sempre utilizzando un numero limitato di risorse e senza stravolgere completamente l'impresa. Elencheremo quindi le soluzioni software attualmente disponibili, mostrandone le loro capacità e vantaggi. Da qui dovremo scegliere quale strumento utilizzare per il nostro progetto, e spiegheremo i motivi che ci hanno portato a prendere questa decisione. Illustreremo la situazione attuale del mercato e ciò che è necessario al giorno d'oggi per essere competitivi, soprattutto rivolto alle tipiche aziende italiane che spesso arrancano di fronte alla concorrenza estera o sono ancora arretrate dal punto di vista tecnologico. Mostreremo quindi un'applicazione pratica di tecniche di analytics in tempo reale, partendo dalla piattaforma scelta, a un database proveniente da un'azienda reale, con l'obiettivo di ottenere insights sulla produzione e l'efficienza, dando una visione chiara ai manager. Infine, ma non meno importante, verrà introdotto il problema dell'integrazione e della qualità dei dati, mostrando una possibile applicazione di queste tecniche al nostro caso di studio.
Managing data variety in an Industry 4.0 case study
PRAVISANO, STEFANO
2018/2019
Abstract
In the recent years the market has changed radically, thanks to technological developments (especially IT) that have made it possible to create a new business model based on highly variable customer needs and the shortening of the product lifecycle. It is with this in mind that the problem of renewing the industry is born, with a new industrial revolution that is bringing and will bring advantages to those who will adapt to it. The starting point was the financing by the Italian government of the development of Industry 4.0, with the creation of a Competence Center at Politecnico di Milano, and other research and industrial centers, that will allow small to medium-sized enterprises (especially in the manufacturing sector) to see the benefits deriving from this new technological-productive innovation. Another important concept we will focus on is Big Data, that is about very large and complex datasets that require different techniques from the traditional ones to capture and analyze data. We will focus in particular on a characteristic of Big Data, the variety, which refers to all structured and non-structured data that can be generated by people or machines. The purpose of this thesis is therefore to show how it is possible to adopt computer engineering solutions to become part of the fourth industrial revolution, however using a limited number of resources and without completely redesigning the enterprise. We will list the currently available software solutions, showing their capabilities and advantages. From this point we will have to choose which tool to use for our project, and we will explain the reasons that led us to make this decision. We will illustrate the current situation of the market and what is necessary nowadays to be competitive, especially focused at the typical Italian companies that often trudge in the face of foreign competition or are still outdated from the technological point of view. We will then show a practical application of real-time analytics techniques, starting from the chosen platform, to a database coming from an existing company, with the aim of obtaining insights on production and efficiency, giving a clear vision to managers. Last, but not least, we will introduce the problem of data integration and quality, showing a possible application of these techniques to our case study.| File | Dimensione | Formato | |
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2019_12_Pravisano.pdf
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https://hdl.handle.net/10589/152441