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Start   >  Master's & postgraduate courses  >  Education  >  Master's degree in Industry 4.0
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  • discount
    15% discount if you enrol before 30th June


3rd Edition
60 ECTS (372 teaching hours)
Language of instruction
€8,300 €7,055(15% discount if you enrol before 30th June)
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
Classes start: 14/10/2022
Classes end: 14/07/2023
Programme ends : 07/10/2023
Friday: 4:00 pm to 9:00 pm
Saturday: 9:00 am to 2:00 pm
Taught at
Why this master's degree?
Industry 4.0 is the body of knowledge formulated by the Fourth Industrial Revolution - the result of the combination between the physical and digital world. Its inevitability is the result of the constant increase in customised demand from markets, which is forcing companies to rethink their production and logistics systems.

The second industrial revolution is taking place in the physical and analogue spheres, with major improvements in the field of design, new materials and new products, and is known as Operations Technology (OT). The third revolution is occurring in the digital domain, has given rise to the "cyber" prefix, and is also known as Information Technologies (IT). Industry 4.0 is therefore a hybridisation of the second and third revolution, and is based on two pillars - on the one hand Cyberphysical systems, and on the other the Internet of Things. The relationship between the "cyber" and physical dimensions is explained by the virtuous circle that is defined by simulation and materialisation.

Modelling enables physical objects to be transferred to the digital world, and simulation techniques used to create "Digital Twins", which are used in high-speed experiments with no physical risk, as well as providing educational, training and support environments for operations through augmented reality and automatic learning (Machine Learning). These can be combined with elements of process modelling, creating a digital value chain. Both the physical world and the simulated world are sources for the generation of large volumes of data (Big Data).

Materialisation means that objects from the digital world can be converted to objects in the physical world, where control of physical objects using software objects is known as automation. Technologies like 3D printing combined with embedded electronics are leading to the emergence of a new generation of connected cyberphysical systems, with technologies such as OPC-UA, enabling Virtual Commissioning and new agile forms of development, in which real objects interact with simulated objects.

The worlds of IT and OT have existed side by side, sharing limited spheres of interaction, and following parallel lives. The demand for cyberphysical systems means that walls that have been in place for decades must be demolished, leading to "IT/OT convergence", which is one of the major challenges posed by Industry 4.0. The figure of the CDO (Chief Digital Officer), also known as the Head of Digital Transformation, is an emerging hybrid professional profile in today's organisation charts. A cross-sectoral approach is one of the motifs of the contemporary world, and Industry 4.0, and Fortune magazine highlights the unstoppable nature of the demand for hybrid professional profiles (Hybrid Jobs).

The main objective of the programme is to train professionals to be able to understand the difficulties and complexities of the world of Industry 4.0 in a cross-disciplinary manner. Participants will obtain the knowledge necessary to create Digital Twins applying simulation and to develop Cyberphysical Systems prototypes for Industry 4.0, using existing digital twins in productive systems and collaborative robotics, 3D printing, embedded systems and sensors to configure networked multi-agent structures, going beyond the traditional hierarchical structures typical of Industry 3.0.

  • Understand the problems of Industry 4.0 and digital transformation processes.
  • Understand when a business problem can be formulated as a platform economy and automation 4.0 problem.
  • Identify the most appropriate automatic learning models and statistical and operational research techniques for a specific problem.
  • Use systems modelling and tools for validating statistics.
  • Use "digital twins" in industrial processes, collaborative robotics and virtual commissioning designs.
  • Know how to prototype and create minimum viable products (MVPs) for the Internet of things (IoT) with embedded electronics and 3D printing.
  • Understand the main regulatory issues that affect an industry 4.0 project.
Who is it for?
  • Operations Technologies Professionals wishing to move into the field of industry 4.0 and obtain the necessary knowledge of Operations Technology.
  • Information Technologies Professionals wishing to move into the field of industry 4.0 and obtain the necessary knowledge of Operations Technology.
  • Entrepreneurs interested in engaging with industry 4.0 and obtaining knowledge of Information Technologies and Operations Technology to that end.
  • Graduates in engineering (computer, telecommunications, industrial, agricultural, civil engineering, etc.), physics, mathematics and statistics.

Training Content

List of subjects
3 ECTS 35h
Industry 4.0, Statistics and Data Management
  • Statistics.
  • Levers of Industry 4.0.
  • Technologies for managing large volumes of data, real-time data management, de-structured data, etc.
  • Data pre-processing:
    • Sources of information and their nature. Data matrix.
    • General pre-processing methodology.
    • Data format operations and software compatibility.
    • Selection of variables, identification of the study population (feature selection and filtering).
    • Identification, diagnosis and treatment of missing data.
    • Identification, diagnosis and treatment of outliers.
    • Reduction of dimensionality.
    • Transformations in data.
    • Creation of indicators, derived variables.
    • Pre-processing procedure design.
    • Automation.
  • Knowledge management.
    • The nature of declarative knowledge.
    • Implicit knowledge.
    • Formal models of knowledge representation.
3 ECTS 18h
Industry 4.0, Fundamentals
  • Basic statistics.
    • Introduction to the distributions of the probability in univariate samples. Discrete and continuous data. Momentum indicators (centred and not centred).
    • The most common discrete distributions: characteristics, use in modelling and identification of profiles: count modelling, modelling the time between events.
    • Samples and populations: sampling vs. inference. Types of sampling. Examples: inference on the mean based on a random sample without/with replacement. Concept of the Hypothesis Test.
  • Introduction to the language R.
4 ECTS 30h
Simulation, Basic Modeling and Programming
  • Definition and use of models with Flexim.
  • Execution of simulation models by hand.
  • Construction of a simulation system by hand.
  • Examples of environmental/social/economic simulation etc.
    • Executing NetLogo models, using systems dynamics models (Insight Maker, etc.)
2 ECTS 12h
Simulation, Basics and Applications
  • DOE.
    • Factorial designs.
    • Fractional factorial designs.
    • Latin squares.
  • RNG/GVA, introduction to complexity theory.
  • Selection and analysis of the sample (input distributions).
  • Introduction to discrete simulation.
    • Definition and use of simulation.
    • Stages in the development of a system.
    • Elements of a simulator.
    • Classic discrete simulation motors (Event Scheduling, Activity Scanning, Process Interaction).
  • Introduction to continuous simulation through the systems dynamics.
  • Introduction to multi-agent simulation.
  • Introduction to cellular automata.
  • Validation, verification and accreditation.
  • Specific simulation tools.
  • Selecting the coding tool (SQMO and others).
  • Examples of simulators in Industry 4.0.
4 ECTS 24h
Introduction to Modeling
  • Data Science.
    • General Data Science process.
    • DMMCM (Data Mining Methods Conceptual Map).
    • Criteria for selecting the most appropriate data exploitation method.
    • Post-procedure and production of value from the data mining model.
  • 3D modelling.
    • Fusion 360.
  • Modelling for simulation systems.
    • Specification and Description Language (SDL).
    • Petri/DEVS networks.
    • Transformation of models.
    • Metamodels/metalanguages.
  • Validation, verification and accreditation issues (HLA and other integration standards).
8 ECTS 60h
Modeling, Digital Twins and Cybersecurity
  • 3D modelling exercises.
    • Fusion 360.
    • Virtual and augmented reality.
  • General modelling of systems.
    • Orientation to Objects.
    • Polymorphism, inheritance.
    • Implementation with ES6.
  • Integration with UML.
    • Structure diagrams.
    • The concept of the metamodel.
    • Behavioural diagrams.
  • Object-oriented analysis and design.
    • Design patterns.
  • Agent-oriented design.
    • Communication between objects.
    • HTTP REST.
  • From formalism to the model: automatic code generation tools.
    • Working with PragmaDEV Studio, SDL, DEVS and Petri Networks.
  • From formalism to the model: general tools.
    • Working with Flexim and NetLogo.
    • Automatic validation of simulation models.
    • Integration with UML.
  • Tools that use the model.
    • HLA standard.
    • Examples of models in SDL.
    • BIM (tools including energy+, NECADA).
4 ECTS 24h
Materialization Technologies 4.0
  • Introduction to the Arduino system.
  • Reference architectures.
    • Background and historical overview.
    • RAMI 4.0
    • IIRA.
8 ECTS 60h
3D printing, Robotics and IoT, Hands on and MVPs
  • 3D printing.
  • Electronic simulation of boards.
  • Systems based on microcontrollers.
    • Arduino microcontrollers, sensors.
    • Arduino PLC.
    • Industrial controllers.
  • Systems based on Operating Systems (Linux).
    • Raspberry Pi.
  • Communications protocols.
    • MQTT.
    • CoaP.
    • Modbus TCP.
  • Web SCADA 4.0.
    • Cloud.
    • Web widgets.
    • Push/Pull GUIs.
  • OPC - UA.
  • Energy infrastructure.
  • Robotics.
  • Public policies.
2 ECTS 12h
Optimization and Big Data Management
  • Smart systems to support decision-making.
  • Simple regression and ANOVA.
  • Introduction to optimisation.
    • Models and types of optimisation problems.
    • Practical resolution of optimisation problems.
  • Basic use of optimisation languages.
4 ECTS 30h
Artificial Intelligence and Optimization
  • Optimisation.
    • Mathematical optimisation models in industry.
    • Advanced use of optimisation languages.
    • Case study: optimal design of the production and distribution chain.
  • Models based on neural networks
2 ECTS 12h
Projects Management. Agile Methodologies
  • Data Law.
  • Computer Security.
  • Internet of Value (Cryptocurrency).
4 ECTS 30h
Project Management. Masterclass
  • Model Based Engineering.
    • PLM.
    • Business models.
    • Repositories of Components and 4.0.
  • Project management philosophies.
    • Scrum, Kambas.
    • Tools for managing Agile projects.
    • Lean Thinking and IoT.
  • Innovation.
    • Development of MVP.
12 ECTS 25h
Final Project
  • Project management.
  • Presentation of the project.
  • Project monitoring sessions.
The UPC School reserves the right to modify the contents of the programme, which may vary in order to better accommodate the course objectives.
Special master's degree issued by the Universitat Politècnica de Catalunya. Issued pursuant to art. 34.1 of Organic Law 4/2007 of 12 April, amending Organic Law 6/2001 of 21 December, concerning Universities. To obtain it, is necessary to have an official university qualification. Otherwise, the student will receive a course completion certificate of the programme issued by the Fundació Politècnica de Catalunya. (Ver datos que constan en el certificado).
Range of modules
The master's degree programme is organized into the following modules. If you don't wish to take the entire master's degree you can sign on one or several modules.
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.
Success stories
Outstanding business knowledge and experiences with high added value acquired during an outstanding professional career are presented and shared.
Problem-based learning (PBL)
An active learning methodology that enables the student to be involved from the beginning, and to acquire knowledge and skills by considering and resolving complex problems and situations.
Flipped classroom
The contents are prepared prior to the face-to-face lessons. Practical sessions take place in the classroom, which enable understanding and application of concepts to real cases and the expansion of knowledge with more technical and specialised details.
Students are given technical support in the preparation of the final project, according to their specialisation and the subject matter of the project.
Students are supported when undertaking group work, including theoretical sessions which provide the tools and knowledge needed to achieve a result. Ideas and results are exchanged between all the participating groups.
Assessment criteria
At least 80% attendance of teaching hours is required.
Level of participation
The student's active contribution to the various activities offered by the teaching team is assessed.
Solving exercises, questionnaires or exams
Individual tests aimed at assessing the degree of learning and the acquisition of competences.
Work out projects
Studies on a specific topic, by individuals or groups, in which the quality and depth of the work is assessed, among other factors.
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 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

Academic management
  • Fonseca Casas, Pau
    View profile in futur.upc / View profile in Linkedin
    Doctor at Statistics and Operative Investigation for the Universitat Politècnica de Catalunya (UPC). Teacher of the UPC where imparts teaching at the area of Simulation, the treatment of data, the Operative Investigation and the Statistics. He¿s Responsible of the Area of Environmental Simulation of the inLab FIB leading projects of simulation linked predominately at industrial and environmental areas. He¿s member of the Commission 4.0 of the Industry of Engineers of Catalonia.
  • Pi i Palomés, Xavier
    View profile in Linkedin
    Industrial Engineer from the Polytechnic University of Catalonia (UPC), judicial expert in Industrial Computing and ICT, has taught Software Engineering at the Faculty of Informatics of Barcelona (FIB-UPC) and at the Open University of Catalonia (UOC). He is a member of the Industry 4.0 Commission of Engineers of Catalonia (, responsible for the Diagnostic 4.0 Working Group ( of the aforementioned commission.
Teaching staff
  • Badia Sendra, David
    View profile in Linkedin
    Industrial Engineer by ETSEIB with a postgraduate degree in Operations and Supply Chain Management by UPC and certified of competency in Manufacturing Operations Management by MESA International. CEO at INLEAN Engineering. Embedded Systems & IoT Workgroup Vocal in Industry 4.0 Commission of Engineers of Catalonia. Technical consultant and trainer in secure communication protocols for Industry 4.0 and building automation like OPC UA. Speaker in conferences of AEFI, MESA and other industry events.
  • Bonastre Majoral, Yair
    View profile in Linkedin
    Industrial Engineer from the Universitat Politècnica de Catalunya. Master in Automated and Robotic Production (PAIR) by the CIM UPC. His professional experience starts in the world of control, supervision and maintenance in the railway field, but he quickly enters the world of emerging technologies such as the Internet of Things (IoT) with its corresponding connectivities and the applicability of Machine Learning, the Deep Learning and Neural Networks to the Industry, Retail or Smart City sectors, both in the computer vision part and in the data part. Currently it is CDO to TEDELOC.
  • Fonseca Casas, Antoni
    View profile in Linkedin
    PhD Architect by the UPC of Barcelona. Specialized in energy optimization and sustainability. It has the Professional Accreditation Diploma and Project Experience of the Leed International certification. Postgraduate degree AECEI C ++ and SQL programming. Quality management certification diploma ISO 9001: 2008. Postgraduate specialization 'Rehabilitation in building', by the UPM. Training in Prevention and Occupational Risks - Safety and health, by the UPC. Collaborator in several universities as researcher and teacher.
  • Fonseca Casas, Pau
    View profile in futur.upc / View profile in Linkedin
    Doctor at Statistics and Operative Investigation for the Universitat Politècnica de Catalunya (UPC). Teacher of the UPC where imparts teaching at the area of Simulation, the treatment of data, the Operative Investigation and the Statistics. He¿s Responsible of the Area of Environmental Simulation of the inLab FIB leading projects of simulation linked predominately at industrial and environmental areas. He¿s member of the Commission 4.0 of the Industry of Engineers of Catalonia.
  • Fontquerni Gorchs, Agustí
    View profile in Linkedin
    Industrial Engineer for the UPC (ETSEIB), Electronic Engineer for the UPC (ETSETB), Industrial Technical Engineer speciality at Industrial Electronics for the UAB (EUSS). Founder and CTO during 10 years at local company manufacturer of embedded complex with export at international customers. Engineer with an experience of more of 20 years at the Industry at the integration of electronics advanced and programming of software at ecosystems GNU/Linux. Accrued experience of 20 years at university teaching of grades and master¿s degrees accredited by the AQU. Technological advisor at the TIC area at the public sector.
  • Gibert Oliveras, Karina
    View profile in futur.upc
    Ph.D. in Computer Science at UPC. Associate Professor at the Dep. Statistics and Operations Research (UPC), leading courses related with her research areas in Degree in Statistics, D. in Informatics Engineering, Master in Informatics Engineering, M. in Artificial Intelligence, M. in Sustainability, all at UPC, and its associated PhD programs. ViceDean for Big Data and Data Science of the Official Professional Chamber of Informatics Engineering of Catalonia. Subdirector of IDEAI Research center (UPC).
  • Heredia Cervera, Francisco Javier
    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.
  • Lloret Garcia, Jose Maria
    View profile in Linkedin
    Engineer at Automatic and Industrial Electronics for it UPC. Master´s degree in Control of Edifices and Sustainable Architecture for it URL. With more of 15 years of experience at software of control, supervision and IoT, at present develops his professional task at Rockwell Automation. Advisor at the companies at his path of automation and digitalization, as well as at the integration of the new techs at the factory, to improve his productivity.
  • Marco Párraga, Daniel
    View profile in Linkedin
    A graduate in Electronic Engineering from the UPC and a Master's Degree in Business Administration from ESADE. He is currently director of the SmartCatalonia strategy for the Government of Catalonia, where he has held other positions in the last 11 years, including head of the ICT Industrial Promotion programmes of the Secretariat for Telecommunications, Cybersecurity and Digital Society. He previously worked in the private sector, holding various positions in the strategic consultancy field in the Information and Communication Technologies sector, and in research and development projects.
  • Montero Mercadé, Lídia
    View profile in futur.upc / View profile in Linkedin
    PhD in Computer Science from the Technical University of Catalonia (UPC). Degree in Computer Science from the FIB-UPC. Professor of Statistics and Operations Research at the UPC since 1998. She teaches on the Master's Degree in Supply Chain, Transport and Mobility at the UPC. Senior Consultant at Advanced Logistics Group (SANO). Experience of more than 25 years in simulation and modelling of problems in public and private transport networks. Transport analytics (data science applied to mobility and transport data) and modelling of transport demand. Collaborator with inLab-UPC.
  • Muñoz Tapia, Jose Luis
    View profile in futur.upc / View profile in Linkedin
    PhD in Telecommunications Engineering from the Technical University of Catalonia (UPC) and professor in the Department of Telematics Engineering at the UPC. His research work is focused on the field of network security, cryptography and the development of secure applications. In this area, he is co-author of dozens of articles in journals and conferences.
  • Peiró i Alemany, Josep Maria
    View profile in Linkedin
    Engineer by the ETSEIB of Barcelona. Specialty Electricity and Power Electronics. Commercial and Marketing Management for EADA Barcelona. He has worked for more than 36 years in multinational companies (SquareD, Telemecanique, Merlin Gerin, Crouzet and Schneider Electric) in the sectors of protection, electrical distribution and automation for buildings and infrastructures, industrial control, machine safety, automation systems of industrial processes and Data center installation systems. He's currently a member of the Energy / Renewable Energy Commission, also member of the SmartCities and Embedded Systems & IOT Working Groups of the Industrial Engineers Association of Catalonia and member of CMES Committee for the new energy and social model.
  • Pi i Palomés, Xavier
    View profile in Linkedin
    Industrial Engineer from the Polytechnic University of Catalonia (UPC), judicial expert in Industrial Computing and ICT, has taught Software Engineering at the Faculty of Informatics of Barcelona (FIB-UPC) and at the Open University of Catalonia (UOC). He is a member of the Industry 4.0 Commission of Engineers of Catalonia (, responsible for the Diagnostic 4.0 Working Group ( of the aforementioned commission.
  • Poch Espallargas, Manel

    Doctor of Science from the Autonomous Universitat Autònoma de Barcelona (UAB). Professor of Chemical Engineering and Director of the Chemical and Environmental Engineering Laboratory (LEQUIA) at the University of Girona.
  • Soler Puig, Carles
    View profile in Linkedin
    Telecommunications Engineer from the Universitat Politècnica de Catalunya (UPC) and Master in Business Administration from the School of Business Administration and Management (ESADE). Most of his career has been spent in management positions in technology services companies. He is currently Director of Casiopea Robotics, a strategic consultancy in collaborative and service robotics, and President of the educaBOT Foundation, a project dedicated to the promotion of technology and engineering through robotics competitions.

Associates entities

Collaborating partners

Career opportunities

  • Chief Digitalization Officer.
  • Chief Information Officer (Industrial).
  • Chief Data Officer (Analyst / Manager of industrial data).
  • Chief Artificial Intelligence Officer (Industrial).
  • Expert in simulation of industrial processes.
  • Chief Technology Officer (Industrial).
  • Chief Product Officer.
  • Chief Operation Officer.
  • Expert in robotics and IoT.

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