A deep learning model for controlling the galvanizing process in a production line

In the industry of steelmaking, the process of galvanizing is a treatment which is applied to protect the steel from corrosion. The air knife effect (AKE) occurs when nozzles emit a steam of air on the surfaces of a steel strip to remove excess zinc from it. In our work we formalized the problem to control the AKE and we implemented, with the R&D dept.of MarcegagliaSPA, a DL model able to drive the AKE. We call it controller. It takes as input the tuple : a tuple of the physical conditions of the process line (t,h,s) with the target value of the zinc coating (c); and generates the expected tuple of (pres and dist) to drive the mechanical nozzles towards the (c). According to the requirements we designed the structure of the network. We collected and explored the data set of the historical data of the smart factory. Finally, we designed the loss function as sum of three components: the minimization between the coating addressed by the network and the target value we want to reach; and two weighted minimization components for both pressure and distance. In our solution we construct a second module, named coating net, to predict the coating of zinc resulting from the AKE when the conditions are applied to the prod. line. Its structure is made by a linear and a deep nonlinear “residual” component learned by empirical observations. The predictions made by the coating nets are used as ground truth in the loss function of the controller. By tuning the weights of the different components of the loss function, it is possible to train models with slightly different optimization purposes. In the tests we compared the regularization of different strategies with the standard one in condition of optimal estimation for both; the overall accuracy is ± 3 g/m^2 dal target for all of them. Lastly, we analyze how the controller modeled the current solutions with the new logic: the sub-optimal values of pres and dist can be optimize of 50% and 20%.

Edge and Big Data technologies for Industry 4.0 to create an integrated pre-sale and after-sale environment

The fourth industrial revolution, also known as Industry 4.0, has rapidly gained traction in businesses across Europe and the world, becoming a central theme in small, medium, and large enterprises alike. This new paradigm shifts the focus from locally-based and barely automated firms to a globally interconnected industrial sector, stimulating economic growth and productivity, and supporting the upskilling and reskilling of employees. However, despite the maturity and scalability of information and cloud technologies, the support systems already present in the machine field are often outdated and lack the necessary security, access control, and advanced communication capabilities. This dissertation proposes architectures and technologies designed to bridge the gap between Operational and Information Technology, in a manner that is non-disruptive, efficient, and scalable. The proposal presents cloud-enabled data-gathering architectures that make use of the newest IT and networking technologies to achieve the desired quality of service and non-functional properties. By harnessing industrial and business data, processes can be optimized even before product sale, while the integrated environment enhances data exchange for post-sale support. The architectures have been tested and have shown encouraging performance results, providing a promising solution for companies looking to embrace Industry 4.0, enhance their operational capabilities, and prepare themselves for the upcoming fifth human-centric revolution.

Progettazione ed Implementazione Front-End di un Sistema Integrato di Customer Assistance in ambito Industry 4.0

Al giorno d'oggi, l'industry 4.0 è un movimento sempre più prominente che induce ad equipaggiare gli impianti industriali con avanzate infrastrutture tecnologiche digitali, le quali operano sinergicamente con l'impianto, al fine di controllare ed aumentare la produttività, monitorare e prevenire i futuri guasti, ed altro ancora. In questo ambito, gli utenti sono parte integrante della struttura produttiva, in cui ricoprono ruoli strategici e flessibili, collaborano fra loro e con le macchine, con l’obiettivo di affrontare e risolvere proattivamente una vasta gamma di problemi complessi. In particolare, la customer assistance nel settore industriale può certamente variare in relazione a molteplici elementi: il tipo di produzione e le caratteristiche del prodotto; l'organizzazione ed infrastruttura aziendale interna; la quantità di risorse disponibili che possono essere impiegate; il grado di importanza ricoperto dalla customer assistance nel settore industriale di riferimento; altri eventuali fattori appartenenti ad un dominio specifico. Per queste ragioni, si è cercato di individuare e categorizzare nel modo più accurato possibile, il lavoro svolto in questo elaborato ed il contesto nel quale è stato sviluppato. In questa tesi, viene descritta un'applicazione web per erogare assistenza al cliente in ambito di industria 4.0, attraverso il paradigma di ticketing o ticket di supporto/assistenza. Questa applicazione è integrata nel sistema Mentor, il quale è attivo già da anni nel settore industriale 4.0. Il progetto Mentor è una suite di applicazioni cloud-based creata dal gruppo Bucci Industries, una multinazionale attiva nell'industria e nell'automazione con sede a Faenza. In questo caso di studio, si presenta la progettazione ed implementazione della parte front-end del suddetto sistema di assistenza, il quale è integrato ed interconnesso con un paio di applicazioni tipiche di industria 4.0, presenti nella stessa suite di applicazioni.

Progettazione e sviluppo di un supporto Industry 4.0 per la manutenzione predittiva di macchine in ambito farmaceutico

La mia tesi riguarda il progetto che ho sviluppato all'interno di IMA Active. Inizia con un'introduzione ai concetti e tecnologie presenti nell'Industry 4.0, ho illustrato i vantaggi dell'utilizzo di piattaforme per il monitoraggio e supporto alla manutenzione predittiva degli asset in ambito aziendale per poi addentrarmi nella demo che ho sviluppato in Python per simulare le funzionalità che dovranno essere implementate in un sistema terzo (di tipo OSISoft Pi). In questo percorso ho introdotto il concetto di DTW e Golden batch che sono stati indispensabili nello sviluppo del progetto.

Modulare Logistiksysteme in der Prozessindustrie unter Einbeziehung von Industrie 4.0

Zur Gewährleistung einer kundenindividuellen, flexiblen Produktion, welche auch kleine Losegrößen kostengünstig produzieren kann, werden zukünftig Fabriken der Prozessindustrie nicht nur modular sondern darüber hinaus mobil sein. Zur Erreichung dieses Zieles werden neben Produktionselemente, auch sämtliche Logistikkomponenten in Containern zu Modulen zusammengefasst. Hierfür ist es notwendig Lager, aber auch komplexe Verpackungsmaschinen, zu konzipieren welche sich zusammen mit Produktionsmodulen, nach dem Plug-and-Produce-Prinzip, zu kompletten Produktionslinien verknüpfen lassen. Die Steuerung und Organisation erfolgt nach den Gedanken von Industrie 4.0.

Industrializzazione di una famiglia di componenti meccanici secondo i principi dell'industria 4.0

Il progetto di tesi tratta l'industrializzazione di una famiglia di componenti meccanici con gli obiettivi di riduzione del lead time e dei costi di produzione ed un miglioramento della qualità costruttiva. Per fare ciò è stato definito un nuovo ciclo di fabbricazione che riunisse tutte le operazioni di asportazione di truciolo in un unico centro di lavoro di fresatura. Sono state definite, progettate e messe in atto tutte le fasi del processo produttivo utilizzando i moderni software CAD-CAM-CNC. Al termine sono stati elaborati i risultati ottenuti svolgendo anche una analisi economica per valutare il risparmio percentuale annuo sul costo di produzione. Infine è stato fatto un confronto fra il vecchio ed il nuovo processo produttivo realizzato secondo i principi dell'Industria 4.0 ed i relativi vantaggi che esso permette di ottenere.

Zielgerechte Logistikkonzepte in Betrachtung von LNG- Umschlageplätzen unter Berücksichtigung von Industrie 4.0

Logistikkonzepte in der Spedition und Transportgewerbe spielen heutzutage eine immer wichtigere Rolle, um Lohnnebenkosten so niedrig wie möglich zu halten. Gerade in der Spedition entsteht ein Zusammenspiel aus zeitnaher Lieferung von Konsumgütern und Optimierung der Lagerhaltungskosten bei dem die modulare Integration von Logistik, Informationstechnischen Systemen und vernetzter Kommunikation eine ganz spezifische Rolle hat. Anbindung von der Industrie zum Kunden wird dadurch immer mehr verstärkt, wobei sich somit dies zusehends zu einem Technologietransfer der Industrie 4.0 entwickelt. Die deutsche Wirtschaft steht augenblicklich am Übergabepunkt zur virtuellen Revolution im Industriezeitalter.

An Image Recognition Software for Identification of Vehicle Homologation Tags

In recent years, we have witnessed great changes in the industrial environment as a result of the innovations introduced by Industry 4.0, especially in the integration of Internet of Things, Automation and Robotics in the manufacturing field. The project presented in this thesis lies within this innovation context and describes the implementation of an Image Recognition application focused on the automotive field. The project aims at helping the supply chain operator to perform an effective and efficient check of the homologation tags present on vehicles. The user contribution consists in taking a picture of the tag and the application will automatically, exploiting Amazon Web Services, return the result of the control about the correctness of the tag, the correct positioning within the vehicle and the presence of faults or defects on the tag. To implement this application we ombined two IoT platforms widely used in industrial field: Amazon Web Services(AWS) and ThingWorx. AWS exploits Convolutional Neural Networks to perform Text Detection and Image Recognition, while PTC ThingWorx manages the user interface and the data manipulation.

Real-time optical monitoring of the dip coating process

A significant part of film production by the coating industry is based on wet bench processes, where better understanding of their temporal dynamics could facilitate control and optimization. In this work, in situ laser interferometry is applied to study properties of flowing liquids and quantitatively monitor the dip coating batch process. Two oil standards Newtonian, non-volatile, with constant refractive indices and distinct flow properties - were measured under several withdrawing speeds. The dynamics of film physical thickness then depends on time as t(-1/2), and flow characterization becomes possible with high precision (linear slope uncertainty of +/-0.04%). Resulting kinematic viscosities for OP60 and OP400 are 1,17 +/- 0,03. St and 9,9 +/- 0,2 St, respectively. These results agree with nominal values, as provided by the manufacturer. For more complex films (a multi-component sol-gel Zirconyl Chloride aqueous solution) with a varying refractive index, through a direct polarimetric measurement, allowing also determination of the temporal evolution of physical thickness (uncertainty of +/- 0,007 microns) is also determined during dip coating.

Aplicación de la metodología Six Sigma para solucionar problemas de calidad en una empresa metalmecánica

En la actualidad muchas compañías enfocan sus esfuerzos en la chequera del cliente generando con esto una cortina de humo al interior de la empresa que hace que se descuiden los costos, se conviva con actividades que no agregan valor y se desconozcan las causas de los principales problemas de calidad que afectan al cliente. Este es el caso de la compañía metalmecánica objeto de esta investigación, la cual venía sobrellevando altos niveles de inventarios, reprocesos, problemas de calidad, falta de corresponsabilidad del personal, y otras situaciones que la estaban dejando vulnerable ante la competencia. Este fue el motivo que inspiró esta investigación en aras de validar una metodología de mejora continua para identificar, analizar, proponer, evaluar y reducir los costos de no calidad y sus implicaciones, de una forma ordenada, rigurosa y disciplinada. Posterior a la implementación del plan de acción los resultados no se hicieron esperar y la compañía mejoró su servicio al cliente sin incurrir en excesos de inventario, al igual que disminuyó sus sobrecostos de producción, los cuales eran generados en gran medida por problemas de calidad. Pero lo más significativo es que asimiló que esta metodología es un proceso continuo que no puede parar y que todo el personal de la empresa debe estar implicado.

Industrie 4.0 Framework, Challenges and Perspectives

The world is increasingly in a global community. The rapid technological development of communication and information technologies allows the transmission of knowledge in real-time. In this context, it is imperative that the most developed countries are able to develop their own strategies to stimulate the industrial sector to keep up-to-date and being competitive in a dynamic and volatile global market so as to maintain its competitive capacities and by consequence, permits the maintenance of a pacific social state to meet the human and social needs of the nation. The path traced of competitiveness through technological differentiation in industrialization allows a wider and innovative field of research. Already we are facing a new phase of organization and industrial technology that begins to change the way we relate with the industry, society and the human interaction in the world of work in current standards. This Thesis, develop an analysis of Industrie 4.0 Framework, Challenges and Perspectives. Also, an analysis of German reality in facing to approach the future challenge in this theme, the competition expected to win in future global markets, points of domestic concerns felt in its industrial fabric household face this challenge and proposes recommendations for a more effective implementation of its own strategy. The methods of research consisted of a comprehensive review and strategically analysis of existing global literature on the topic, either directly or indirectly, in parallel with the analysis of questionnaires and data analysis performed by entities representing the industry at national and world global placement. The results found by this multilevel analysis, allowed concluding that this is a theme that is only in the beginning for construction the platform to engage the future Internet of Things in the industrial environment Industrie 4.0. This dissertation allows stimulate the need of achievements of more strategically and operational approach within the society itself as a whole to clarify the existing weaknesses in this area, so that the National Strategy can be implemented with effective approaches and planned actions for a direct training plan in a more efficiently path in education for the theme.

Homogeneous photodegradation of CI Reactive Blue 4 using a photo-Fenton process under artificial and solar irradiation

The oxidation of C.I. Reactive Blue 4 (RB4) by photo-Fenton process mediated by lerrioxalate was investigated under artificial and solar irradiation. The RB4 degradation in acidic medium (pH 2.5) was evaluated by the decrease in Total Organic Carbon (TOC) content and color, measured by the decrease in chromophore absorption band (600 nm). The influence of ferrioxalate and H2O2 concentrations on the dye degradation was studied and best results were obtained using 1.0 mM ferrioxalate and 10 nM of hydrogen peroxide. Under these experimental conditions, 80% of TOC and 100% of color removal were obtained for a 0.1 mM RB4 dye in 35 min of solar irradiation. (c) 2006 Elsevier Ltd. All rights reserved.

Preparation of 9/65/35 PLZT thin films deposited by a dip-coating process

Crack-free polycrystalline PLZT (Pb,a)(Zr,Ti)O-3 thin films with the perovskite structure were prepared by dir-coating using the Pechinis process. Lead acetate, hydrated lanthanum carbonate, zirconium n-propoxide and titanium isopropoxide were used as raw materials. The viscosity of the solution was adjusted in the range of 20 to 56 cP and the films were deposited by a dip-coating process on silicon (100) as substrate. Solutions with ionic concentration of 0.1 and 0.2 M were used. Thin film deposition was accomplished by dipping the substrates in the solution with control of withdrawal speed from 5 to 20 mm/min. The thin films were thermally treated in two steps: at 300 degreesC amid 650 degreesC. The influence of withdrawal speed. viscosity, heating rate and ionic concentration on the morphology of PLZT thin film was discussed. (C) 2001 Elsevier B.V. Ltd. All rights reserved.

GDP 4.0 transfer to SGP 3.0 for SCIAMACHY no2 column processing: Verification with SDOAS / GDOAS prototype algorithms and delta-validation with NDACC / UV-visible network data

Until mid 2006, SCIAMACHY data processors for the operational retrieval of nitrogen dioxide (NO2) column data were based on the historical version 2 of the GOME Data Processor (GDP). On top of known problems inherent to GDP 2, ground-based validations of SCIAMACHY NO2 data revealed issues specific to SCIAMACHY, like a large cloud-dependent offset occurring at Northern latitudes. In 2006, the GDOAS prototype algorithm of the improved GDP version 4 was transferred to the off-line SCIAMACHY Ground Processor (SGP) version 3.0. In parallel, the calibration of SCIAMACHY radiometric data was upgraded. Before operational switch-on of SGP 3.0 and public release of upgraded SCIAMACHY NO2 data, we have investigated the accuracy of the algorithm transfer: (a) by checking the consistency of SGP 3.0 with prototype algorithms; and (b) by comparing SGP 3.0 NO2 data with ground-based observations reported by the WMO/GAW NDACC network of UV-visible DOAS/SAOZ spectrometers. This delta-validation study concludes that SGP 3.0 is a significant improvement with respect to the previous processor IPF 5.04. For three particular SCIAMACHY states, the study reveals unexplained features in the slant columns and air mass factors, although the quantitative impact on SGP 3.0 vertical columns is not significant.

SmartForge: An event-driven architecture for simulator-based process optimization

In the metal industry, and more specifically in the forging one, scrap material is a crucial issue and reducing it would be an important goal to reach. Not only would this help the companies to be more environmentally friendly and more sustainable, but it also would reduce the use of energy and lower costs. At the same time, the techniques for Industry 4.0 and the advancements in Artificial Intelligence (AI), especially in the field of Deep Reinforcement Learning (DRL), may have an important role in helping to achieve this objective. This document presents the thesis work, a contribution to the SmartForge project, that was performed during a semester abroad at Karlstad University (Sweden). This project aims at solving the aforementioned problem with a business case of the company Bharat Forge Kilsta, located in Karlskoga (Sweden). The thesis work includes the design and later development of an event-driven architecture with microservices, to support the processing of data coming from sensors set up in the company's industrial plant, and eventually the implementation of an algorithm with DRL techniques to control the electrical power to use in it.