Costruzione di un sistema per l'alimentazione dei materiali alla produzione: il caso Bosch Rexroth Oil Control S.p.A.

Il seguente elaborato è il risultato di uno stage di sei mesi, svolto presso l’azienda Bosch Rexroth Oil Control S.p.A.. L’ente presso cui è stato svolto il tirocinio è l’Industrial Engineering. In particolare è stata compiuta un’analisi dei flussi delle cartucce meccaniche, una famiglia di valvole oleodinamiche. Il lavoro si è sviluppato in tre fasi: nella prima è stata fatta un’analisi dei dati di giacenza, tempi e cicli di lavoro delle cartucce; nella seconda fase si è proposta l’introduzione di un nuovo sistema di picking gestito con supermarket a kanban; nell’ultima fase si è valutata la convenienza dai punti di vista tecnico ed economico del progetto.

Outdoor production of Isochrysis galbana (T-iso) in industrial scale photobioreactors and modelling of its photosynthesis and respiration rate

Isochrysis galbana is a widely-used strain in aquaculture in spite of its low productivity. To maximize the productivity of processes based on this microalgae strain, a model was developed considering the influence of irradiance, temperature, pH and dissolved oxygen concentration on the photosynthesis and respiration rate. Results demonstrate that this strain tolerates temperatures up to 35ºC but it is highly sensitive to irradiances higher than 500 µE·m-2·s-1 and dissolved oxygen concentrations higher than 11 mg·l-1. With the researcher group of the “Universidad de Almeria”, the developed model was validated using data from an industrial-scale outdoor tubular photobioreactor demonstrating that inadequate temperature and dissolved oxygen concentrations reduce productivity to half that which is maximal, according to light availability under real outdoor conditions. The developed model is a useful tool for managing working processes, especially in the development of new processes based on this strain and to take decisions regarding optimal control strategies. Also the outdoor production of Isochrysis galbana T-iso in industrial size tubular photobioreactors (3.0 m3) has been studied. Experiments were performed modifying the dilution rate and evaluating the biomass productivity and quality, in addition to the overall performance of the system. Results confirmed that T-iso can be produced outdoor at commercial scale in continuous mode, productivities up to 20 g·m-2·day-1 of biomass rich in proteins (45%) and lipids (25%) being obtained. The utilization of this type of photobioreactors allows controlling the contamination and pH of the cultures, but daily variation of solar radiation imposes the existence of inadequate dissolved oxygen concentration and temperature at which the cells are exposed to inside the reactor. Excessive dissolved oxygen reduced the biomass productivity to 68% of maximal, whereas inadequate temperature reduces to 63% of maximal. Thus, optimally controlling these parameters the biomass productivity can be duplicated. These results confirm the potential to produce this valuable strain at commercial scale in optimally designed/operated tubular photobioreactors as a biotechnological industry.

Study of nanostructured targets for plasma production via laser ablation

Metal nanowires (NWs) - nanostructures 20-100 nm in diameter and up to tens of micrometers long - behave as waveguides when irradiated with light with wavelength much greater than their diameter. This is due to collective excitations of free electrons (plasmons) in the metal which couple to light and travel on the surface of the nanowire. This effect can be used to efficiently absorb laser pulses to produce dense and hot plasma on special nanostructured targets with metal nanowires vertically aligned on the surface. In this thesis work, nanostructured targets with different parameters (length, diameter, metal and fabrication process) have been irradiated with infrared laser light. X-ray flux emitted by the cooling plasma is measured during irradiation, and the depth of craters formed on the target is measured later. This data is used to choose which target parameters are best for plasma production. Different targets are compared with each other and against a control, non-nanostructured (bulk) target. As will be shown, highly significant (> 5 sigma) differences are found between targets with different nanostructures, and between nanostructured and bulk target. This differences are very difficult to explain whithout accounting for the nanostructures in the targets. Therefore, data collected and analized in this thesis work supports the hypotesys that nanostructured targets perform better than bulk targets for laser plasma production purposes, and provides useful indications for optimization of NWS' parameters.

Industrial Demilitarized Zone and Zero Trust cybersecurity models for Industrial Control Systems

Today more than ever, with the recent war in Ukraine and the increasing number of attacks that affect systems of nations and companies every day, the world realizes that cybersecurity can no longer be considered just as a “cost”. It must become a pillar for our infrastructures that involve the security of our nations and the safety of people. Critical infrastructure, like energy, financial services, and healthcare, have become targets of many cyberattacks from several criminal groups, with an increasing number of resources and competencies, putting at risk the security and safety of companies and entire nations. This thesis aims to investigate the state-of-the-art regarding the best practice for securing Industrial control systems. We study the differences between two security frameworks. The first is Industrial Demilitarized Zone (I-DMZ), a perimeter-based security solution. The second one is the Zero Trust Architecture (ZTA) which removes the concept of perimeter to offer an entirely new approach to cybersecurity based on the slogan ‘Never Trust, always verify’. Starting from this premise, the Zero Trust model embeds strict Authentication, Authorization, and monitoring controls for any access to any resource. We have defined two architectures according to the State-of-the-art and the cybersecurity experts’ guidelines to compare I-DMZ, and Zero Trust approaches to ICS security. The goal is to demonstrate how a Zero Trust approach dramatically reduces the possibility of an attacker penetrating the network or moving laterally to compromise the entire infrastructure. A third architecture has been defined based on Cloud and fog/edge computing technology. It shows how Cloud solutions can improve the security and reliability of infrastructure and production processes that can benefit from a range of new functionalities, that the Cloud could offer as-a-Service.We have implemented and tested our Zero Trust solution and its ability to block intrusion or attempted attacks.

Application of the Extended Kalman filter for speed sensorless control of PM synchronous machines

The increasing interest in the decarbonization process led to a rapidly growing trend of electrification strategies in the automotive industry. In particular, OEMs are pushing towards the development and production of efficient electric vehicles. Moreover, research on electric motors and their control are exploding in popularity. The increase of computational power in embedded control hardware is allowing the development of new control algorithm, such as sensorless control strategy. Such control strategy allows the reduction of the number of sensors, which implies reduced costs and increased system reliability. The thesis objective is to realize a sensorless control for high-performance automotive motors. Several algorithms for rotor angle observers are implemented in the MATLAB and Simulink environment, with emphasis on the Kalman observer. One of the Kalman algorithms already available in the literature has been selected, implemented and benchmarked, with emphasis on its comparison with the Sliding Mode observer. Different models characterized by increasing levels of complexity are simulated. A simplified synchronous motor with ”constant parameters”, controlled by an ideal inverter is first analyzed; followed by a complete model defined by real motor maps, and controlled by a switching inverter. Finally, it was possible to test the developed algorithm on a real electric motor mounted on a test bench. A wide range of different electric motors have been simulated, which led to an exhaustive review of the sensorless control algorithm. The final results underline the capability of the Kalman observer to effectively control the motor on a real test bench.

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%.

Enhancing the value of lignocellulosic biomasses through the production of bionanocomposites

The aim of this work was to optimize a methodology to extract cellulose and to produce NC, from different lignocellulosic biomasses (sorghum, Sorghum bicolor (L.) Moench and sunn hemp, Crotalaria juncea L.). In addition, the NC produced was tested as a reinforcing agent in chitosan (Ch) films, to understand its effects on the properties of this biopolymer. The nanoparticles obtained from sorghum and sunn hemp were incorporated in Ch films at a rate of 2.5% w/w of chitosan, and the resultant bionanocomposites (Sorghum NC films and sunn hemp NC films) were fully characterized in terms of their morphology, mechanical and optical properties, permeability (water vapor), water wettability, and FT-IR spectra analysis. Chitosan films reinforced with commercial nanocellulose at the same rate were tested for comparison, as well as pristine chitosan (control). Bionanocomposites made from sorghum and sunn hemp NC were slightly more saturated and opaque than the pristine chitosan films, in particular outer sorghum NC films. Sunn hemp NC films also showed a slightly higher thickness than sorghum NC films and pristine chitosan films. Further, the results confirmed that sorghum NC improved the strength and stiffness of the chitosan biopolymer and that sunn hemp NC improved the plasticity of the chitosan polymer. Hence, results indicate that those lignocellulosic crops may afford a source of NC for the production of bionanocomposites. Considering the application of those bionanocomposites by the food packaging industry, sorghum NC - chitosan films showed more promising results than sunn hemp NC-chitosan films.