Academic Supervisor:
Saioa Arrizabalaga

department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management

area thematic:
Industrial process modeling. Cybersecurity.

Description and objectives:
Hybrid testbeds allow the study of offensive and defensive cybersecurity mechanisms in industrial environments and also their impact on the process being attacked or defended.
This project would be focused on the generation of digital twins for industrial systems (such as wind turbines, water distribution networks...), using existing Simulink models. The student will have to map sensors/actuators on the models, define operating states (normal, abnormal) to improve testbed monitoring and response capabilities, analyze potential system cybersecurity threats and develop mitigation strategies. Simulink models will be modified so that they can be integrated into the virtualized testbed so that they can be operated in real time.
 

Academic Supervisor:
Luis Vitores Valcárcel García

department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management

area subject:
Mathematical Optimization, Data Science

Description and Objectives:
This project has as goal to develop a system that uses Large Language Models (LLMs) to automatically classify sections of a document, which are not complete chapters, but intermediate parts (such as subsections, paragraphs or fragments) of agreement with criteria defined by the Username. For example, the system will be able to identify and classify content sections such as "methodology", "results", "discussion", among others, according to the characteristics of the text.
Through the use of fine-tuning on pre-trained models, the model will be able to label each section according to topics (technology, health, Economics, etc.) or subject of content (informative, argumentative, descriptive, etc.), allowing a more structured organization and analysis of long documents.
Suggested student activities:

• Literature review on text classification, document segmentation and use of LLMs.

• Data preprocessing: Segmentation of documents into sections (not complete chapters) and labeling of data.

• development from model: Fine-tuning of a pre-trained LLM to classify the sections according to the criteria defined by Username.

• Training and evaluation: Evaluate model performance using metrics such as accuracy, recall, and F1-score.

•  Implementation of an interface or API: Allow the Username to define the classification criteria and upload documents to classify the sections automatically.

•     6. Analysis and improvement of model: Adjust model according to the results obtained, improving classification and accuracy.

Academic Supervisor:
Luis Vitores Valcárcel García

department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management

area subject:
Mathematical Optimization, Data Science, Environmental Engineering.

Description and objectives:
The use of Generative Adversarial Networks (GANs) in the context of wastewater treatment plants allows the generation of realistic meteorological and influent data from historical time series. These networks can generate synthetic data that simulate actual operating conditions, which facilitates analysis and simulation without the need for constant new data. These generated data can feed reduced order models (ROMs), improving the accuracy of simulations.
In addition, the project can be extended to predict the influent from entrance as a function of meteorological variables, allowing the simulators to be used to optimize plant operation over the following days.
Proposed student activities:

• Literature review on the use of GANs in the generation of data for plant simulation.

• development of a GAN to generate realistic meteorological and influent data.

• Integration of the data generated in plant simulators.

• Extension of model to predict influent from meteorological data.

• Evaluation of results and comparison of the accuracy of the generated models.

Academic Supervisor:
Itxaro Errandonea / Luis Vitores Valcárcel García.

department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management

area subject:
Artificial Intelligence, Data Science, Machine Learning.

Description and objectives:
Many real industrial processes can be mathematically formulated by complex mechanistic models composed of nonlinear differential equations. Although these models are very useful to carry out studies of design and operation, their handicap is their high computational cost which makes them unfeasible for use in real-time decision making.
With the advent of Deep Learning techniques, proposals have emerged to reduce the complexity of these models and thus the computational cost. The task of this PFG will be to use the technique known as "physics informed neural networks" to obtain a reduced model of a water treatment plant. The Python environment will be used to carry out the project .

Academic Supervisor:
Luis Vitores Valcárcel García

department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management

area subject:
Mathematical Optimization, Data Science, Environmental Engineering.

Description and objectives:
In wastewater treatment plants in Spain, the volume of incoming and discharged water is recorded daily, generating a continuous database on the influent and effluent of these facilities. To perform simulations and predictions in these plants, mechanistic models based on principles of Biochemistry, thermodynamics and fluid mechanics are used. However, one of the main challenges is that there is no direct correspondence between the available laboratory measurements and the variables needed in the models. This gap prevents accurate calibration of the model, affecting the quality of the simulations.
The project addresses this problem through an influent self-calibration technique, in which the entrance variables in the models are automatically adjusted from the experimental data obtained. This process, similar to a deconvolution, has the goal of improving the accuracy of the simulations and their predictive capability, offering a model adapted to the specific conditions of each plant.
Suggested activities for the student:

• Literature review on self-calibration and deconvolution techniques applied to water treatment plants.

• Mathematical formulation of the influent self-calibration problem.

• Implementation of model in R or Python.

• Analysis of results, evaluating the accuracy and effectiveness of model in specific scenarios.

Academic Supervisor:
Luis Vitores Valcárcel García

department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management

area subject:
Mathematical Optimization, Data Science

Description and objectives:
The application of time-dependent covariates in survival analysis has improved the prediction of time to default in behavioral credit scoring models. However, when these covariates are endogenous, two problems occur: estimation bias and the lack of a framework to predict the future values of the event and the covariates.
Joint models are a statistical approach that simultaneously integrates longitudinal and survival data, allowing to model the joint evolution of an event of interest (such as time to default) and endogenous time-dependent covariates. This project explores for the first time the application of discrete-time joint models to credit scoring, and proposes a novel extension by including autoregressive terms in the endogenous covariates.
The project will apply these methods to U.S. mortgage data, evaluating whether discrete-time joint models improve predictive accuracy compared to traditional survival models and whether performance is optimized by including an autoregressive term.
Proposed student activities:

1. Literature review on conjoint models and their application in credit scoring.

2. Mathematical formulation of the model set in discrete time.

3. Implementation of model in R or Python.

4. Analysis of results, comparing predictive performance against other models.

This project will allow the student to explore advanced statistical modeling techniques applied to financial data and improve predictions in the context of credit risk.

Academic Supervisor:
Luis Vitores Valcárcel García

department Tecnun/Division CEIT:
ICT Division. Group of data analysis and Information Management

area subject:
Mathematical Optimization, Data Science

Description and objectives:

The maintenance scheduling problem, known as the Maintenance Scheduling Problem, consists of optimally organizing maintenance activities within a schedule. This problem seeks to minimize interruptions and operating costs, ensuring that both preventive and corrective maintenance are performed at the right times.
The goal of this end of Degree project is to develop an optimization tool that addresses efficient scheduling of maintenance schedules. The tool will be developed preferably in Python, with additional Matlab or R options.
Proposed student activities:

1. Bibliographic review of the most common optimization problems and algorithms applied in maintenance scheduling.

2. Mathematical formulation of the problem, establishing the relevant criteria and restrictions.

3. Implementation of the solution using a heuristic optimization algorithm or open source solvers.

4. Analysis of results and comparison of the effectiveness of the applied approach , with recommendations for its use in different maintenance situations.

Academic Supervisor:
Markos Losada

department Tecnun/Division CEIT:
Transport and Energy Division: Transport and Sustainable Mobility Group.

area subject:
design electronic, coding, data processing

Description and objectives:
The approach of this final work of Degree focuses on the analysis of advanced distance estimation technologies that could be integrated into a system for a wristband to analyze the game of Padel. The project is divided into several phases, starting with a comprehensive analysis of existing commercial systems, evaluating their advantages and proposing improvements. The review of current technologies such as time-of-flight (ToF), Lidar and ultrasound sensors is fundamental to select the most appropriate technology for this purpose. The proposal for improvement will include technology selection, the development of a specific algorithm and system integration, considering factors such as size, cost and power consumption. The goal is for the student to not only gain knowledge about these technologies, but also to propose a concrete solution that can be implemented.

In the implementation phase, the student will be responsible for integrating the selected sensors and developing a system capable of detecting a matrix of points to accurately estimate distances. The results obtained will be analyzed to evaluate the effectiveness of the proposed algorithm and determine the feasibility of its implementation in a commercial product. This project not only seeks to improve the paddle tennis playing experience, but also to explore potential applications of these technologies in other fields, such as weighing or wagon monitoring.

Academic Supervisor:
Iñigo Adín

department Tecnun/Division CEIT:
Transport and Energy Division: Transport and Sustainable Mobility Group.

area subject:
Artificial intelligence learning, coding, data processing.

Description and objectives:
This final work of Degree has as main goal the development and the implementation of machine learning models in low power microcontrollers, specifically of the STM32 family, using TensorFlow Lite. The project focuses on the application of these models in the transportation sector, with a particular approach on the analysis and improvement of automatic braking systems.
To achieve this goal, the student should:

Training in Tools and Technologies:
Acquire knowledge of TensorFlow Lite for microcontrollers, through Machine Learning resources such as Andrew Ng's documentation, and "Machine Learning with Scikit-Learn, Keras and TensorFlow", as a foundation and using Wes McKinney's "Python for the data analysis" as reference letter for management and data analysis.

development of Machine Learning Models:
Design and train machine learning models that can be optimized for execution on low-power microcontrollers.
Evaluate the performance of these models in terms of accuracy, efficiency and energy consumption. For this purpose, data will be collected with a sensorized brake bench and the models will be trained with them.

Integration in Microcontrollers:
Implement the developed models on STM32 microcontrollers using TensorFlow Lite. Ensure that the integration is efficient in terms of resources and reliability of the results.

Application in the Transportation Sector:
Apply integrated models to improve the automatic braking function in vehicles, analyzing real-time data to optimize system safety and efficiency.
Evaluate the impact of the implementation in test scenarios, adjusting the models as needed to improve performance.

The documentation and results will be organized documenting the references and the process of development. The results obtained will be presented, highlighting the improvements achieved in the automatic braking function and possible future applications of the developed technology.

Academic Supervisor:
Ainhoa Cortés/Juan Manuel Galán

department Tecnun/Division CEIT:
Materials and Manufacturing Division : Intelligent Systems for Industrial 4.0 Group.

area subject:
design electronics, embedded systems

Description and Objectives:
The goal of this PFG is to take contact from student with the RISC-V architecture, its features and its use in embedded systems. For this purpose, a comparison of (at least) a commercial RISC-V based microcontroller against RISC-V CEIT, a RISC-V microcontroller developed at CEIT. This work will attempt to identify differences in various aspects such as (but not limited to):

• Functionality (ISA Extensions, Peripherals, Pinout...)
• Frequency of work
• Consumption (taking into account the available working modes)
• Tools for development

In addition, the student should propose improvements to the design microcontroller developed in-house to improve the deficits revealed from the above comparison.

Academic Supervisor:
Andoni Irizar/Juan Manuel Galán.

department Tecnun/Division CEIT:
Materials and Manufacturing Division : Intelligent Systems for Industrial 4.0 Group.

area subject:
design electronics, embedded systems

Description and objectives:
Within one of the research lines of CEIT, a RISC-V based microcontroller has been developed currently available for Xilinx and Microchip FPGAs. The main goal of this PFG is the adaptation of this microcontroller to FPGA Altera by means of: 

• Analysis of Altera FPGA features

• Identification of the microcontroller elements to be adapted (parameters, macros...)

• development of simulation scripts and functional verification

• development of synthesis scripts and constraints (timing and pinout)

• Synthesis and plate verification

Academic Supervisor:
Juan Manuel Galán/Andoni Irizar.

department Tecnun/Division CEIT:
Materials and Manufacturing Division : Intelligent Systems for Industrial 4.0 Group.

area thematic:
Embedded systems

Description and objectives:
Within one of the research lines of CEIT, a RISC-V based microcontroller (RISC-V CEIT) has been developed. The main goal of this PFG is the development of a bootloader for this microcontroller. Some of the activities to be performed are: 

• development and verification bookshop SW (in C) for access to report Flash.

• development bootloader capable of loading SW via UART and SPI (among other functions)

• Gap analysis development U-boot for RISC-V CEIT

Academic Supervisor:
Emilio Sanchez Tapia

department Tecnun/Division CEIT:
Materials and Manufacturing Division: Robotics and Industrial Control Group.

area thematic:
Robotic Engineering

Description and objectives:
In the context of robotics in the 21st century, the concept of the connected factory arises where machines, mobile robots and humans coexist. Mobile robots may or may not include a robotic manipulator arm or MoMa (MObile MAnipulator). If there is only the mobile robot, it is usually referred to as AMR (Autonomous Mobile Robot) or AGV (Autonomous Guide Vehicle) according to its Degree of freedom in navigation (see figure below). 

Figure 1: Constituent elements of a platform-mounted collaborative robot (or MoMa).
The main application of this device subject is to increase the level of factory automation in sectors where today automation has leave penetration, such as intralogistics and machine tending. In these scenarios, the robot can move raw materials, products in the manufacturing process or even search for machine replacement parts (such as a cutting head for a CNC). In any case, the MoMa will be able to perform the task either autonomously or as an assistant to a human operator (see figure below).

Figure 2: Factory scenario where a MoMa becomes one more resource of the factory where it can work alone or in collaboration with other human operators.
A likely scenario is that in the factory we will find more than one mobile robot, each of them with different capabilities and probably from different manufacturers. In this case it is important to have software that coordinates the tasks and distributes them appropriately according to the availability and/or capacity of each robot. Such software is known as a robot fleet manager.

Figure 3: A fleet manager coordinates the work of a set of robots.

There are many fleet management solutions on the market, but they are usually proprietary and compatible with only one brand of robot.

The goal of the final project of Degree is to deploy and test an open-source robotic fleet manager. The tests will be done both in simulation and with real robots.

As of essay of this document, it is planned to use open-rmf (Open-RMF: https://www.open-rmf.org/ ) or equivalent, see the following figure.

Figure 4: Screenshot of a simulation of coordinated fleets from open-rmf.

It is offered, during the execution of project:

• Incorporation to the robotics group of researchers from the CEIT 

• Training in the software/hardware tools employed 

• Possibility of a job offer in a company in the sector.

Academic Supervisor:
Sebastian Gutierrez.

Group of Tecnun:
Control and Robotics Group of the department of Mechanical Engineering and Materials from TECNUN.

area subject:
Automation and Electronic Systems Engineering.

Description and objectives:

The goal of this PFG is to align with the evolution towards Industry 4.0 in the field of robotics, which is revolutionizing the way companies design, produce and distribute their products. In this context, advances in robotics are playing a key role by enabling the integration of a wide variety of sensors and actuators into industrial robots. The combination of the Internet of Things (IoT), cyber-physical systems and cloud computing provides these robots with the ability to efficiently collect and analyze data, facilitating informed decision-making and the optimization of manufacturing processes.

This project focuses on the implementation of an adaptive gripper that integrates as a slave device with a master industrial robot, which is controlled by a BECKHOFF automaton. Using the protocol EtherCAT, it seeks to leverage these advanced technologies to improve automation and optimize system performance in modern manufacturing environments.

Academic Supervisor:
Enrique Castaño Carmona

Division CEIT:
Advance Powder Metallurgy and Laser Manufacturing Group

area thematic:
Computing, modeling and simulation

Description and objectives:
The machining of materials using ultra-short pulse lasers is a very recent technology development and opens multiple possibilities in the field of functional surfaces, such as low friction coefficient surfaces in wind turbines or anti-icing surfaces in aeronautics. 

Currently, Ceit is leading a European project in which one of its objectives is to develop a simulation software for the machining process with this subject of lasers. The mathematical modeling of the process is already well advanced, as well as its numerical implementation.
The task of this PFG will be to design and develop the graphical interface with the Username of the simulation program so that its use is easy and intuitive. The student will apply and extend his knowledge of Python programming, GUI (Graphic User Interface) and design UX/UI (User Experience/User Interface) to achieve an interface that allows Username an attractive experience of the simulation program.

Academic Supervisor:
Yuemin Ding

department Tecnun:
Electrical and Electronic Engineering

area thematic:
Telecommunication

Description and objectives:

Online monitoring and data collection in ultra-remote areas is specifically meaningful to investigate the local characteristics of climate change, biodiversity evolution, etc. It is also very important to prevent huge disasters, such as wildfires. However, online monitoring and data collection in ultra-remote areas have been challenging during the past decades. A major challenge is the lack of digital infrastructure for communication and data collection. However, the emerging satellite networking (such as Starlink) and low-power and long-distance IoT (such as MIoTy) technologies enable an alternate solution for online monitoring and data collection. The aim of this project is to develop a system based on satellite networks and low-power and long-distance IoT to enable online monitoring and data collection in ultra-remote areas.

Academic supervisor:

Íñigo Adín

Division CEIT:

ICT Division

area thematic:

IoT, communications, low power, Bluetooth.

Description and objectives:

This project proposes the evaluation of Bluetooth 5.1 technology in its modality Long Range for use in industrial environments. The aim here is to see the possibilities of this longer range version to compete in IoT technologies to be installed in production plants or in remote sensors, with range for the admissible meters in this case.

The aim is to evaluate this technology using evaluation boards and configuring the elements at FW and SW level to measure the signal quality in parameters potentially useful in industrial applications (time of flight, data rate, packet error rate, etc.). To do this, a search for these evaluation boards will be proposed and programming will be required using the admissible interfaces in each case.

Academic supervisor:

Ainara Rodríguez - Isabel Ayerdi

Division CEIT:

Materials and Manufacturing. Advanced Manufacturing in Powder Metallurgy and Laser Group.

Description and objectives:

Laser functionalization of surfaces is an approach widely used in a wide variety of applications and sectors, as it allows to provide final products with added functionalities, including, among others, decorative effects, the ability to repel liquids or improve the adhesion of coatings. At the moment Ceit is developing an international project of research and development in this last field, whose goal is to improve the adhesion of antibacterial and antiviral coatings to high traffic objects such as handles, switches or push buttons.

In the framework of this project in cooperation, a TFG is proposed whose goal is the design and implementation of a test bench for the characterization of the surface properties of the manufactured samples, among which are the improvement of adhesion, hydrophobicity/hydrophilicity characteristics or optical properties among others. In addition to the above, it will be necessary to implement an intelligent processing system for the data obtained by the measuring elements.

Academic supervisor:

Yago Olaizola

Division CEIT:

Materials and Manufacturing. Advanced Manufacturing in Powder Metallurgy and Laser Group.

Description and objectives:

Transparent materials are currently used in a multitude of applications in which their optical properties are particularly relevant: lenses, devices for optical communications, smart glasses or optical sensors, among others. In this context, the characterization of the optical properties is a point core topic in the development of the devices.

The goal of this project will be to design and implement an optical microscopy system, starting from different optical and mechanical elements, for the analysis of certain properties of transparent materials. After the validation of the equipment, we will proceed to study the optical behavior of this substrate subject after different laser engraving processes. In parallel, it will be necessary to implement an intelligent processing system for the data obtained by the measurement devices.

Academic supervisor:

Gemma García Mandayo

Division CEIT:

Materials and Manufacturing. Advanced Manufacturing in Powder Metallurgy and Laser Group.

Description and objectives:

The project is framed within the development of an innovative system for the measurement of erythrocyte sedimentation rate (ESR) and coagulation, for application in clinical diagnostics. The main purpose of the system is to provide results of ESR and/or blood coagulation in a minimum time, with a minimum amount of sample and using sustainable materials, offering significantly higher performance than the devices currently available in the market, and thus allowing a faster and earlier diagnosis of pathologies such as infections, tumors or autoimmune diseases.

The goal of project is the optimization of the sample characterization processes, developing a test bench and performing tests to improve the performance of the device.

Academic supervisor:

Íñigo Adín

Division CEIT:

ICT

area thematic:

NDT, RF, Transport

Description and objectives:

This project aims to design a system for detecting cracks in railway rails. At the level of the basic principle of detection, it is proposed here to be carried out by means of a radar technique in radio frequency technologies with the capacity to illuminate the rail in movement. The reflections received must be processed to determine the presence of cracks smaller than the size specified in the regulations before grinding the rail. With this project, the aim is to advance in the specification of the basic principle of detection, and to investigate the needs for mounting on a moving element.

Academic supervisor:

Íñigo Adín

Division CEIT:

ICT

area thematic:

IoT, Energy Harvesting, low energy consumption

Description and objectives:

This project proposes the acquisition and implementation of novel platforms for the transformation of motion, radio frequency, sound or wind into energy usable by autonomous IoT systems. There are currently more integrated and more efficient platforms that promise to provide power to electronic data collection and remote connection systems and it is important to know the real scope of their possibilities. This refers here to testing and merging the possibilities of taking advantage of unusual physical elements/events for these applications, to replace the usual solar panels.

Academic supervisor:

Leticia Zamora Cadenas - Iker Aguinaga Hoyos.

Division CEIT:

Information and Communication Technologies. Intelligent Systems for Industry 4.0 Group.

area thematic:

Telecommunication/Industrial Engineering

Description and objectives:

Indoor location systems are a booming element in recent years. Whether using radiofrequency technologies, inertial sensors or artificial vision systems, the location of objects or people in interior spaces is an element core topic in many applications (tracking of parts, access to security areas, tracking of people, augmented reality, etc.).

To determine and evaluate the accuracy of a location system, the most common method is to measure guide a number of control points or tests in a controlled environment to determine the accuracy of the system. However, this subject measurement is always subject to measurement errors, human error, and the impossibility of tracking a moving element in real time. Another widespread option, especially when the accuracy is to be evaluated dynamically, is to resort to cost-effective systems that allow the creation of the real path or "ground truth", such as, for example, vision tracking systems. However, it is not always possible to deploy this type of system subject , or the economic means to do so are not always available. Therefore, being able to evaluate the accuracy of indoor positioning systems at a low cost is still a problem that researchers and companies are trying to solve.

Currently Ceit has a line of research associated with positioning systems for indoor spaces, in which it works with various companies to provide solutions to their needs. This is why the need for a ground truth system that is easy to install and not too expensive was born.

The task of this GFP would be to develop a ground truth system, using virtual/augmented reality systems, for subsequent use in evaluating the accuracy of the proprietary indoor location system Ceit. HTC Vice, Oculus Quest and Hololens 2 hardware are available for the development of this system using the Unity3D programming platform. The candidate must have programming skills in C# or similar languages such as C++ or Java.

Academic supervisor:

Emilio Sánchez Tapia

Division CEIT:

Information and communications technologies. Intelligent Systems for Industry 4.0 Group. Vision and Robotics Subgroup

area thematic:

Robotics Engineering

Description and objectives:

Industry 4.0 has paved the way for multiple forms of automation that have as goal improve productivity and optimize work processes. In this context, the aim is to develop an intelligent mobile manipulator: a new robot subject that integrates the technology of an autonomous mobile robot and a highly efficient collaborative robotic arm capable of performing various operations.

The idea of project is to develop a robot that can move, detect and avoid obstacles, explore its environment to recognize objects through artificial vision and perform part handling tasks, being able to interact with operators. With the idea of implementing a digital transformation model , required today in real factory environments, robots, control elements, sensors and other onboard elements will be connected to each other through a digital platform to control the process in real time and from anywhere.

Currently CEIT has already developed a first working prototype (see figure below).

The task of this GFP would be the programming under ROS-2 of a sequence of tasks for the robot to interact with a classic robotic cell. The specific case to be developed will be for the robot to go to a archive of parts to be processed, bring them to the cell, wait for their processing and take them to another storeroom of already sorted parts.

Under this simple task, the concepts of:

• Collaborative mobile robotics
• Machine tending
• Control in force
• Problem of synchronisation of two automatic devices

Programming skills in C/C++, Python or java-script are required.

Academic Supervisor: Gurutz Artetxe.

Division CEIT: Electric Vehicle and Smart Grids.

area subject: Electrical Engineering.

Description and Objectives: Induction heating is an efficient and fast method of generating heat. It can be employee in various applications where tempering, brazing or melting of metals is required. CEIT is interested in developing computational tools (based on a set of previously developed tools) for use in the design of induction heating systems for formwork. The goal of this project is to model the electromagnetic and heating behavior of a formwork heating system and to perform optimization studies with them in order to carry out the design of a practical case.

• profile/Degree: Industrial Technologies, Mechanics, Electricity, Industrial Electronics.
• Academic Supervisor: Juan Carlos Ramos.
• department/area: department of Mechanical Engineering and Materials / area of Thermal and Fluid Engineering.
• Description: The aim is to solve by means of the Finite Difference Method a thermal model of the generation and conduction of heat in the core and coils inside a transformer. The equations of the model and the solution by the iterative Gauss-Seidel method will be implemented in Matlab. Heat transfer issues will be applied. For further information please contact the professor.

Academic supervisor:

Andoni Irizar

department Tecnun/Division CEIT:

CEIT. Materials and Manufacturing Division

area thematic:

Electronic systems

Description and objectives:

In today's industrial processes it is increasingly necessary to monitor the manufacturing process and the quality of the components resulting from the process. There are a wide variety of methods that allow such monitoring in real time, that do not require separating the parts from the rest for analysis and that do not damage the parts in the process. The most commonly used inspection techniques are those using electromagnetic fields, ultrasonic signals and machine vision. This project deals with ultrasonic techniques. The Ceit has its own ultrasonic signal test bench that allows to generate and capture ultrasonic signals in a simple way from a PC. The goal of project will consist of making a proposal of design of a miniaturized test bench (for example, the size of a Raspberry). As a comparison, the current design occupies the size of a Desktop computer. It would involve making a block diagram of the system, making a selection of components including the processing platform to be used and the components of the power source . Finally, it will be necessary to estimate the consumption and cost of the final equipment.

Academic supervisor:

Jorge Juan Gil.

department Tecnun/Division CEIT:

CEIT. Intelligent Systems for Industry 4.0 Group.

area thematic:

Systems and Control Engineering

Description and objectives:

So far the control concepts are shown on the blackboard, by means of simulations or with videos. For the Control Engineering subject we want to build a mechanical control system (two pendulums coupled with springs) to be used for teaching purposes: to show in class the different behavior of the system before several controllers. To ensure portability, the system will be controllable through USB by means of an ARDUINO card . In a previous project the mechanical system has been built. In the proposed project several controllers will be programmed in C, in particular, a proportional-integral (PI) controller that allows "teleoperation" (that the Username moves one of the pendulums and the other one follows its movement without error in permanent regime).