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Start   >  Master's & postgraduate courses  >  Education  >  Continuing education master's degree in Technologies Applied to Mechatronics 4.0
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    10% discount if you enrol before 1 July

Presentation

Edition
23th Edition
Credits
60 ECTS (450 teaching hours)
Delivery
Blended learning
Language of instruction
Spanish
Fee
€8,200 €7,380(10% discount if you enrol before 1 July)
Payment of enrolment fee options

The enrolment fee can be paid:
- In a single payment to be paid within the deadline specified in the letter of admission to the programme.
- In two instalments:

  • 60% of the amount payable, to be paid within the deadline specified in the letter of admission to the programme.
  • Remaining 40% to be paid up to 90 days at the latest after the starting date of the programme.
- In four instalments, splitting the payment by direct debit:
  • 40% of the amount payable, to be paid within the deadline specified in the letter of admission to the programme.
  • The remaining 60% will be divided into 3 direct debit payments, which will be distributed equidistantly between the beginning and end of classes.
  • The student must have and be the holder of a bank account with IBAN ESXX
Notes 0,7% campaign

Registration open until the beginning of the course or until end of vacancies.
Start date
Start date: October of 2024
End date: April of 2026
Timetable
Monday: 6:00 pm to 9:30 pm
Tuesday: 6:00 pm to 9:30 pm
Wednesday: 6:00 pm to 9:30 pm
Thursday: 6:00 pm to 9:30 pm
Taught at
ETSEIB - Escola Tècnica Superior d'Enginyeria Industrial de Barcelona
Av. Diagonal, 647
Barcelona
Why this continuing education master's degree?
The industry is a sector in continuous transformation that is currently undergoing a paradigm shift. In fact, for a few years the term industry 4.0 has been coined, which refers to its full immersion in the fourth industrial revolution. The leap to industry 4.0 is born hand in hand with the digital age and evolves towards data science (data science), with key concepts such as big data or machine learning. In other words, today's industry is becoming an integrated and intelligent industry.

Classical mechatronics are based on four fundamental pillars: mechanics, electronics, control and computing. However, to obtain the maximum productive and energy efficiency in a set of industrial equipment, it is necessary to know the devices and understand their operating principles. Even so, this vision is today biased and, in a way, obsolete. In the current scenario, it is necessary to complement this knowledge with a deep understanding of the possibilities of interconnection with other existing devices in order to achieve higher performance and improve flexibility through industrial digitization. If we add data science concepts to all this, a transversal, multidisciplinary profile is configured and adapted to the new needs that we call mechatronic industrial designer in the era of digitized industry.

The master's degree in Technologies Applied to Mechatronics 4.0 seeks to go one step beyond classical mechatronics. For this reason, he provides designers of industrial machines and products, traditionally focused on the mechanical field, with all the necessary skills to become the figure of the mechatronic industrial designer that Industry 4.0 needs. To this end, the contents of the master's degree focus both on classical mechatronics and on providing a more digital and innovative vision, integrating data science tools and knowledge applicable to the industry.

The program provides innovative solutions in technologies applied to mechatronics and the most advanced knowledge in industrial communications, computer languages and environments used in the industrial environment, as well as new data processing techniques such as machine learning, big data or digital twins, among others.

Promoted by:
Aims
  • To integrate electronics, informatics and communications technology into the design of a component or mechanical system.
  • To design mechatronic components and systems that are better adapted to product needs.
  • To automate the function of mechanical systems and make it possible for them communicate with their environment.
  • Present and contract the sensorized information of the machines for their use.
Who is it for?
  • Engineers.
  • Professionals in the economic sector with technical vision.
  • Professionals in the technical field.

Training Content

List of subjects
12 ECTS 105h
+
Blended learning
Elements of Mechatronic Systems
  • Introduction and Basic Concepts
    • Introduction to electrotechnics.
    • Introduction to electronics.
    • Introduction to simulation with Matlab / Simulink.
- Sensors

    • Presence sensors.
    • Position, speed and acceleration sensors.
    • Deformation, force and pressure sensors.
    • Temperature, flow and level sensors.
    • Sensors of electrical magnitudes.
    • Sensor connection.
    • Electric actuators
    • Constituent materials of electric actuators: conductors, dielectric and magnetic.
    • DC motor.
    • Synchronous motor, brushless DC and brushless AC.
    • Induction motor.
    • Selection of motors based on kinematic chains.

- Hydraulic and Pneumatic Automation and Drives

    • General concepts of hydraulics, pumps and fluid treatment.
    • Elements of hydraulic circuits and systems and typical applications.
    • Selection of elements and design of hydraulic circuits and systems.
    • General concepts of pneumatics, compression and air treatment.
    • General pneumatics elements: valves and components.
    • Design of pneumatic automation.
    • Safety in pneumatic applications.
    • General electropneumatic elements: electrovalves, relays and electromechanical logic.
    • Design of electropneumatic automation.
    • Energy saving in pneumatics.
    • Power Electronics
  • Introduction to static converters.
    • Basic typologies.
    • Real switches: trip and protection.
    • Other elements in power electronics.
    • DC / DC, DC / AC and AC / DC converters.
    • Converter design.
    • Applications.
12 ECTS 112h
+
Blended learning
Control and Automation of Mechatronics Systems
  • Introduction to Programmable Controllers
    • Introduction to automation and programming languages.
    • Introduction to programming languages: Graphics (Ladder (LD)), Functional Blocks (FBD, Grafcet) and textual (structured, ST) and list of instructions (IL).
    • First steps in the programming of industrial automatons.
    • Ladder programming practices and use of standard counter or timer-type functional blocks (TON, TOFF and TP).
    • Automation design in Grafcet.
    • Introduction to the IEC61131 standard.
    • The Gemma Guide.
    • Introduction to programming a stepper motor and HMI (Human Machine Interface) interfaces.
  • Application of Industrial Programmable Automatons
    • Programming for the application / process layer of a stepper motor.
    • Automation of a flexible production cell based on electric and electro-pneumatic actuators.
    • Automation and control of an induction motor controlled by a variator: open loop and implementation of a PID.
    • Application of the Gemma Guide.
  • Control of Dynamic Mechatronic Systems
    • Standard models of dynamic systems.
    • Single Input Single Output Systems (SISOs).
    • The transfer function. Stability. Standard systems of order 1 and 2.
    • The PID controller.
    • Interpretation of performance or sensitivity functions.
    • Control in state space.
    • Linearization for non-linear systems.
  • Digital Control of Mechatronic Systems
    • Hybrid systems.
    • Introduction to digital control and the Z transform.
    • The order maintainer 0 and its model.
    • Manipulation of transfer functions in z.
    • Stability and tuning.
    • Correspondence between domains (Laplace - Z).
    • Implementation of functions in Z to difference equations.
    • o Digital filters: FIR (Finite Impulse Response) and IIR (Infinite Impulse Response).
    • o Examples of discrete time control and implementation in DSP.
12 ECTS 112h
+
Blended learning
Elements for Digitization in Industry
  • Microcontrollers and Programmable Logic
    • Basic concepts of microcontrollers, types and structure of memory, types of inputs and outputs, programming languages.
    • Logic functions and Boolean logic.
    • Combinational and sequential systems. Flip-flops, registers and counters.
    • Formats for saving data, format changes, direct and indirect addressing, program counter.
    • Main modules and tools: oscillator, timers, comparators, A / D and D / A converters, PWM, communications, interruptions, watchdog timer, standby mode, real-time clock, management of flash memories and EEPROM.
    • Assembler programming, RISC instructions, examples.
    • C programming, examples.
  • Data Acquisition
    • Introduction to data acquisition systems.
    • Acquisition in the temporal domain.
    • Programming of acquisition systems with labview.
    • Signal acquisition and treatment with Matlab.
  • Digital Signal Controllers (DSCs)
    • Introduction to DSC.
    • Configuration of the DSC and its peripherals.
    • Fixed point libraries (IQmath).
    • DSC peripherals aimed at motor control.
  • Industrial Communications
    • Introduction to telecommunications.
    • Power Line Communication (PLC).
    • Ethernet and TCP / IP.
    • Cybersecurity in the industrial environment.
    • Fieldbus concepts.
    • CAN, Modbus and CANOpen.
12 ECTS 91h
+
Blended learning
Management of Mechatronic Systems in a Digital Environment
  • Mathematical Principles and Optimization Tools
    • Basic principles of optimization.
    • Mathematical, deterministic and heuristic formulations.
- Information Technology

    • Introducció a les TICs (Virtualització, Linux).
    • Introduction to programming (language C).
    • Repository management (GIT).
    • Data Bases.
    • Design of web pages (HTML and CSS).
    • Programming languages: PHP and Javascript.

- Introduction to Big Data and Machine Learning

    • Introduction to Python.
    • Data visualization for Data Science.
    • Introduction to Big Data and Machine Learning: basic concepts, learning types, data pipeline and fields of application.
    • Descriptive statistics for data analysis. Understanding, cleaning and pre-processing of data.
    • Supervised learning models: regression.
    • Supervised learning models: classification.
    • Unsupervised learning models: clustering, dimensionality reduction.
  • Industrial applications of Machine Learning
    • Digital twin.
    • Predictive maintenance: installation of sensors, data monitoring and performance of a failure prediction algorithm.
    • Artificial intelligence for component design.
12 ECTS 30h
+
Blended learning
Master Project
With the final project, students worked for a reminder of the agenda for the postgraduate and demonstrates that it has acquired the necessary knowledge.
The UPC School reserves the right to modify the contents of the programme, which may vary in order to better accommodate the course objectives.
Degree
Continuing education master's degree issued by the Universitat Politècnica de Catalunya. Issued by virtue of the provisions of art. 7.1 of Organic Law 2/2023 of 22 March, concerning the University System, and art. 36 of Royal Decree 822/2021 of 28 September, which establishes the organisation of university education and the procedure for ensuring its quality. A prior official university qualification is necessary to obtain it. Otherwise, the student will receive a certificate of completion of the course issued by the Fundació Politècnica de Catalunya. Lifelong learning studies at the Universitat Politècnica de Catalunya are approved by the University's Governing Council on an annual basis. (See details appearing on the certificate).
Range of modules
The continuing education master's degree programme is organized into the following modules. If you don't wish to take the entire continuing education master's degree you can sign on one or several modules.
Continuing education master's degree:
relation Postgraduate courses:

Learning methodology

The teaching methodology of the programme facilitates the student's learning and the achievement of the necessary competences.



Learning tools
Participatory lectures
A presentation of the conceptual foundations of the content to be taught, promoting interaction with the students to guide them in their learning of the different contents and the development of the established competences.
Practical classroom sessions
Knowledge is applied to a real or hypothetical environment, where specific aspects are identified and worked on to facilitate understanding, with the support from teaching staff.
Solving exercises
Solutions are worked on by practising routines, applying formulas and algorithms, and procedures are followed for transforming the available information and interpreting the results.
Case studies
Real or hypothetical situations are presented in which the students, in a completely participatory and practical way, examine the situation, consider the various hypotheses and share their own conclusions.
Visits
These visits are to specialist centres, companies in the sector or outstanding and important locations in the sector, in order to obtain knowledge in situ of development, production and demonstration environments within the programme.
Streaming sessions
Synchronous online interactive open sessions will be planned. Professors attend these sessions and students pose questions and address their concerns. Synchronous sessions will be scheduled in calendar.
Assessment criteria
Attendance
At least 80% attendance of teaching hours is required.
Solving exercises, questionnaires or exams
Individual tests aimed at assessing the degree of learning and the acquisition of competences.
Completion and presentation of the final project
Individual or group projects in which the contents taught in the programme are applied. The project can be based on real cases and include the identification of a problem, the design of the solution, its implementation or a business plan. The project will be presented and defended in public.
Work placements & employment service
Students can access job offers in their field of specialisation on the My_Tech_Space virtual campus. Applications made from this site will be treated confidentially. Hundreds of offers of the UPC School of Professional & Executive Development employment service appear annually. The offers range from formal contracts to work placement agreements.
Virtual campus
The students on this continuing education master's degree will have access to the My_ Tech_Space virtual campus - an effective platform for work and communication between the course's students, lecturers, directors and coordinators. My_Tech_Space provides the documentation for each training session before it starts, and enables students to work as a team, consult lecturers, check notes, etc.

Teaching team

Teaching staff
  • Chillón Antón, Cristian
    info

    Industrial Engineer from the Polytechnic University of Catalonia (UPC). Project Engineer at CITCEA-UPC specialized in converter control algorithms. Experience working on projects developing microgrids, active filters, photovoltaic converters, electric vehicle and storage systems chargers.
  • de la Mata García, Domingo Jesús
    info
    View profile in Linkedin
    Graduated in computer engineering from the Polytechnic University of Catalonia (UPC). He is currently a Technical Engineer for CITCEA-UPC.
  • Díaz González, Francisco
    info
    View profile in futur.upc / View profile in Linkedin
    Doctor in Industrial Engineering from the Polytechnic University of Catalonia (UPC). Professor of the Department of Electrical Engineering of the UPC and member of the Center for Technological Innovation in Static Converters and Drives (CITCEA-UPC). Ten years of experience in the application of energy storage systems in renewable generation systems and electrical networks.
  • Fillet Castellà, Sergi
    info
    View profile in futur.upc
    Industrial Engineer from the Universitat Politècnica de Catalunya (UPC). Professor of Electrical Engineering at the UPC.
  • Galceran Arellano, Samuel
    info
    View profile in futur.upc
    Ph.D. in Industrial Engineering from the Universitat Politècnica de Catalunya. Assistant Professor University and creator of CITCEA-UPC.
  • Heredia Cervera, Francisco Javier
    info
    View profile in futur.upc / View profile in Linkedin
    Graduated in Physical Sciences from the University of Barcelona (UB) and Doctor in Operations Research from the Polytechnic University of Catalonia (UPC). Associate Professor in the Department of Statistics and Operations Research at the UPC. His area of interest is mathematical optimization models and algorithms applied to problems in energy systems (renewable energy, electricity market), and supply chain (Industry 4.0). He has participated in a total of 17 funded research projects, seven of them as principal investigator, in collaboration with various companies in the energy sector and industrial production.
  • Jené Vinuesa, Marc
    info
    View profile in Linkedin
    Double Master in Energy Engineering from the Katholieke Universiteit Leuven (KUL) and the Universitat Politècnica de Catalunya (UPC), within the Energy for Smart Cities (EIT InnoEnergy) program. Degree in Engineering in Industrial Technologies from the UPC. He is currently part of the team of the Center for Technological Innovation in Static Converters and Drives (CITCEA-UPC) and works on Big Data projects applied to the energy industry. He has been selected to participate in various entrepreneurship programs such as the Red Bull Basement and the InnoEnergy Entrepreneurship Journey.
  • Llonch Masachs, Marc
    info

    Industrial Engineer from the Universitat Politècnica de Catalunya (UPC). Senior project engineer at CITCEA-UPC. With six years of experience in the design and development of electric power converters, both connected to the network and for motor control. His main research has focused on microgrids, switching strategies for three-phase inverters and electric mobility, providing several publications on the subject. Currently, he also teaches industrial control in the master's degree in Automated Production and Robotics at CIM-UPC.
  • Martin Segura, Guillermo
    info
    View profile in Linkedin

    Doctor of Engineering from the Universitat Politècnica de Catalunya (UPC). Industrial engineer from the UPC. More than ten years of experience in the field of power electronics.

  • Miguel Espinar, Carlos
    info
    View profile in futur.upc / View profile in Linkedin

    Doctor in Electrical Engineer by Universitat Politècnica de Catalunya (UPC) focuses his research on the design and control of power electronics. As a Senior Project Manager at CITCEA-UPC, he leads cutting-edge Power Electronics and Drives initiatives. His expertise includes developing control strategies and power electronics for electric machines in EVs, renewable energy integration, induction heating, and drives. He possesses a strong background in designing electrical machines for various applications, such as drives, ventilation, hydraulics, and appliances.

  • Montesinos Miracle, Daniel
    info
    View profile in futur.upc / View profile in Linkedin
    Ph.D. Electrical Engineering from the Universitat Politècnica de Catalunya. Professor in the Department of Electrical Engineering of the UPC.
  • Prieto Araujo, Eduardo
    info
    View profile in futur.upc
    Doctor in Electrical Engineering from the UPC. Reader professor in the Electrical Engineering Department of the UPC. Researcher of the CITCEA-UPC.

Associates entities

Collaborating partners

Career opportunities

  • Expert in quality and industrial maintenance.
  • Supervisor of production control systems and machines.
  • Consultant specializing in the design and control of automated systems.
  • Data analyst for industrial processes.

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Once the fee has been paid and we have all your documentation, we will assess your candidacy and, if you are admitted on the course, we will send you a letter of acceptance. This document will provide you with all the necessary information to formalize the enrolment process for the programme.




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