Ottimizzazione di un Sistema di Key Performance Indicators per la Divisione Engineering aziendale. Il caso INTERTABA S.p.A.

Il seguente elaborato è la diretta conseguenza di un periodo di stage, pari a cinque mesi, svolto presso l’azienda INTERTABA S.p.A., a Zola Predosa (BO). Il Dipartimento presso cui è stato svolto il tirocinio è l’Engineering. In particolare è stata compiuta un’analisi dei KPIs presenti e sono state proposte delle azioni migliorative. Il lavoro si è sviluppato in tre fasi. Nella prima fase è stata fatta un’analisi dei KPIs attuali per ciascuna funzione appartenente all’Engineering: Engineering Support, Project Engineering, Plant & Utilities Maintenance, Technical Warehouse e General Services. Nella seconda fase sono state descritte, per ciascuna funzione, alcune proposte migliorative per i KPIs presenti. Infine, per alcune funzioni, sono state proposte alcune iniziative in merito all’implementazione di nuovi KPIs.

Environmental impact assessment of the School of Engineering and Architecture (Lazzaretto) - A pathway towards LEED certification

The current work has for object the improvement and the maintenance of the School of Engineering and Architecture in Via Terracini 28 (Bologna), with the prospective to maximize the operative efficiency reducing to the minimum the environmental impact and the costs. In order to realize this work the LEED certification has been used. LEED (Leadership in Energy and Environmental Design) is a certification system of the buildings. It was born in United States by the U.S. Green Building Council (USGBC)

Analysis ot the road barriers maintenance: the Bologna Case Study

This thesis deals with the topic of Road Safety when maintaining its road elements. The aim of the work is the prioritization of maintenance for each barrier that depends on some factors that are related to the topography of the site, deformations, degradation of the composing elements, and the compliance of the barrier installation with the original situation. Based on these components a final coefficient by which the maintenance priority was highlighted, calculated, and associated to each barrier. For easy study and visualization, information was uploaded and processed in a GIS environment, in order to create analyses and choropleth maps. Analyses were exploited by using free and open-source GIS software, namely QGIS. Information on the barriers' features was registered with both on-site and online (i.e., web mapping providers) inspections. With regards to the on-site inspections, a complete geotagged photos database was created, in order to improve the survey. GIS potentialities were fully exploited by applying some geoprocessing tools which allowed deep analyses.

Acquisition of Vibration Signals for Predictive Maintenance: a Practical Case

As predictive maintenance becomes more and more relevant in industrial environment, the possible range of applications for this maintenance strategy grows. The progresses in components technology and their reduction in price, together with the late years' advances in machine learning and in computational power, are making the implementation of predictive maintenance possible in plants where it would have previously been unreasonably costly. This is leading major pharmaceutical industries to explore the possibility of the application of condition monitoring systems on progressively less and less critical equipment. The focus of this thesis is on the implementation of a system to gather vibrational data from the motors installed in a pre-existing machine using off-the-shelf components. The final goal for the system is to provide the necessary vibration data, in the form of frequency spectra, to a machine learning system developed by IMA Digital, which will be leveraging such data to predict possible upcoming faults and to give the final client all the information necessary to plan maintenance activity according to the estimated machine condition.