Use of cookies

We use our own and third-party cookies to improve our services. You can get more information and set your preferences.
Information on our cookies policy

Reject Cookies
Accept Cookies

Campus in maintenance
User and / or password incorrect
You have no active environment
Your access has been restricted. Consultation with the department of administration
Due to technical problems, the virtual campus is inaccessible. We are working to solve it. Sorry for the inconvenience.
Start   >  Master's & postgraduate courses  >  Education  >  Postgraduate course in Modeling and Simulation in Industry 4.0
Request information
Request information Request information or admission
Apply for admission
Apply for admission
This postgraduate course is also part of the training track for the master's degree in Industry 4.0.


Information 2021-2022 edition
The 2021-2022 edition of the postgraduate course has already begun. Shortly we will publish updated information about the new edition of this programme.
2nd Edition
24 ECTS (179 teaching hours)
Language of instruction
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 60 days at the latest after the starting date of the programme.
Notes 0,7% campaign

Registration open until the beginning of the course or until end of vacancies.
Next course
October 2022
Friday: 4:00 pm to 9:00 pm
Saturday: 9:00 am to 2:00 pm
Taught at
Why this postgraduate course?
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).

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 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 from the physical world to the digital world, applying simulation as a basic tool in the process. The participants will obtain the knowledge necessary to develop cybernetic system models for Industry 4.0 and Digital Twins.
  • Understand the problems of Industry 4.0 and digital transformation processes.
  • Practice with cutting-edge simulation tools.
  • Create "Digital Twins" for industrial elements and processes.
  • Use 3D modelling systems.
  • Identify the most appropriate automatic learning models and the statistical and operational Research techniques for a specific problem.
  • Be able to perform pre-processing of data and identify Big Data approaches.
  • Use systems modelling and statistical validation systems and tools and be able to verify and validate the proposed models.
Who is it for?
  • Operations Technology Professionals wishing to enhance their IT knowledge base in the field of data processing, modelling and simulation for Industry 4.0.
  • Information Technologies Professionals wishing to acquire knowledge of the OT world of industrial process modelling.
  • Graduates in engineering (computer, telecommunications, industrial, agricultural, civil engineering, etc.), physics, mathematics and statistics.

Training Content

List of subjects
3 ECTS 18h
Industry 4.0 and Society
  • 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.
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.
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 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.)
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 and Digital Twins
  • 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).
Postgraduate diplomas 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 this degree it is necessary to have an official. Otherwise, the Fundació Politècnica de Catalunya will only award them a a certificate of completion. (Ver datos que constan en el certificado).
Range of modules
This postgraduate course is part of the training track for the master's degree in Industry 4.0 .
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.
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 postgraduate course 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.
Teaching staff
  • 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.
  • 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).
  • Medina Llinàs, Manel
    View profile in futur.upc
    Professor at the Polytechnic University of Catalonia (UPC) since 1992 and Scientific Coordinator of the European Chapter of the Anti-Phishing Working Group (APWG). Since 1994 he has led the CERT-UPC, the first incident response team in Spain. He has worked as an expert on NIS and was head of the CERT liaison unit at ENISA (European Union Agency for Cybersecurity). He also led scientific security projects at the Barcelona Digital Technology Centre. As a member of ESRIF (European Security Research & Innovation Forum) and ESRAB (European Security Research Advisory Board) (2006-2009) he collaborated with the European Commission on security research programmes.
  • 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.

Associates entities

Collaborating partners

Career opportunities

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

Request information or admission

Request received!
After we have registered your request, you will receive confirmation by email and we will be in touch.

Thank you for your interest in our training programmes.
Due to an error in the connection to the database, your submission has not been processed. Please try again later, phone us on (34) 93 112 08 08, or send us an email at:
You have exceeded the maximum size of the file
  • If you have any doubts about the postgraduate course.
  • If you want to start the registration procedure.
How to start admission
To start the enrolment process for this programme you must complete and send the form that you will find at the bottom of these lines.

Next you will receive a welcome email detailing the three steps necessary to formalize the enrolment procedure:

1. Complete and confirm your personal details.

2. Validate your curriculum vitae and attach any additional required documentation, whenever this is necessary for admission.

3. Pay €110 in concept of the registration fee for the programme. This fee will be discounted from the total enrolment fee and will only be returned when a student isn't admitted on a programme.

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.

  date protection policy

* Mandatory fields

Información básica o primera capa sobre protección de datos


Fundació Politècnica de Catalunya (en adelante, FPC). + INFORMACIÓN


Contestar a las solicitudes de información del interesado sobre actividades de formación gestionadas o realizadas por la FPC. + INFORMACIÓN

Establecimiento o mantenimiento de relación académica con el interesado. + INFORMACIÓN


Consentimiento del interesado. + INFORMACIÓN

Interés legítimo en el desarrollo de la relación académica. + INFORMACIÓN


No existen cesiones o comunicaciones.


Acceso, rectificación, supresión, limitación, oposición y portabilidad. + INFORMACIÓN

Datos de contacto del delegado de protección de datos

Información adicional

Política de Privacidad de nuestra página Web. + INFORMACIÓN

Plazo de conservación

Política de Privacidad de nuestra página Web. + INFORMACIÓN

Cesión de imagen

Aceptación a la cesión, por un periodo de 10 años, las imágenes que la FPC pueda captar en las instalaciones donde se desarrolle su actividad, a fin de difundir y promocionar las actividades de la FPC y por el medio que esta tenga por conveniente.

Servicios de pago

En caso que el interesado formalice la relación con la FPC, el ordenante (interesado) autoriza y da su consentimiento al cargo, por tanto, con renuncia expresa al derecho de devolución sobre el cargo.