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Automation and industrial informatics are multidisciplinary subjects that rely over the traditional engineering discipline, yet demanding a high expertise and know-how about information and communication technologies (ICTs).

ICTs play an increasingly major role in industry due to the need for higher productivity, better quality, more cost effective maintenance, increasing safety, higher energy efficiency, and in general, in all the aspects of this business, which most challenging issue arises from the necessity for integration of heterogeneous information.

Thus, this Masters degree in Automation Engineering and Industrial Informatics is designed to provide the graduates in industrial engineering or computer science with the capabilities and skills to face challenging automation and monitoring projects taking optimal advantage of such new technologies.

What is MAIIND’s Added Value?

MAIIND students will complete their curriculum with a global vision of the production system, its implications with the overall logic structure of the plant information, the devices and instruments used for its acquisition, treatment, and decision-making. ICTs play a major role in this process, as they are the underlying and facilitating technologies.

To these knowledge and advanced capacities, MAIIND will add to the student’s curriculum all necessary know-how on applying and integrating such technologies with automation and monitoring disciplines, and the overall production process management.

Hands-on and industry cooperation

A sustainable learning can only be reached by hands-on application of knowledge. That’s why all courses schedule a significant number of hands-on classes where the student will use real equipment and advanced tools to solve complex problems, which require the progressive integration of partial solutions.

Industry cooperation is a key point for a successful and useful learning process. The cooperation will not only come in the form of seminars and classroom talks, but also by offering internships for the students, which will allow them to gain labour experience while fulfilling some compulsory credits.

Prospective students profile

This masters degree is oriented to graduate students in industrial engineering and computer science with a major in control theory, programming languages, and industrial processes.


Graduate students profile


MAIIND Structure

Modules description and temporal sequence

This is a three semester masters degree (90 ECTS credits). The two first semesters are devoted to classroom lessons, while the third one is entitled for the students to gain a practicum experience at a company, where they will carry out an internship (12 ECTS credits) and develop their final project (18 ECTS credits).

M1 – Remedial Courses

Home and Building Automation

Automation and Process Control

M2 – Common Technologies

M3 – Advanced Automation

M4 – Advanced Supervision

M5 – Complementary Technologies Industrial

Informatics Systems

M6 - Internship

M7 – Final Dissertation

6 Elective

9 Elective

9 Elective

36 Compulsory

12 Compulsory

18 Compulsory

Total: 90 ECTS

6 6





Data Visualization Control Systems State Space

Embedded Systems

Digital Signal

Processing Intelligent Manufacturing Systems Business Management Information Systems Scientific Research Aspects Energy Efficiency In Industry Analysis and Implementation of Automation Systems Industrial Software Development Industrial Inspection Systems Advanced Technologies for System Integration Plants and Industrial Processes Advanced Methodologies for Automation

Safety in Automation

3D Computer Vision

Intelligent Techniques for Industrial Inspection 4,5 4,5 3 3 3 3 3 3 3 3 3

9 6

6 6

9 First Semester (1st year) Second Semester (1st year) Third Semester (2nd year) Virtual Instrumentation 3



Module 1: Remedial Courses (6 ECTS Credits)

This module contains fundamental courses that provide the students with two options. Those students with a major in industrial engineering or a close discipline will take the course

Industrial Informatics Systems in order to acquire the basic competences that will allow them to understand and use the necessary ICTs to successfully attend this master.

Those students with a major in computer science or a close discipline will take the course

Automation and Process Control in order to acquire the basic competences about automation engineering and process control theory subjects, which will allow them to successfully attend this master.

Module 2: Common Technologies (36 ECTS Credits)

This is the core module that enables the student to acquire a set of common competences, which are considered fundamental for such a wide discipline as automation engineering and industrial informatics.

In this module the students will get to know and understand the different types of productive plants and industrial processes. They will be able to apply advanced analysis and design technologies for integration of systems with a special emphasis in the development of industrial software that enable them to accomplish data exploitation, and process control and supervision applications.

Besides, the students will acquire enabling competences for the systemic development of the control logic of industrial process by applying normalised techniques expressed in formal languages and implementing them using standard design patrons or architectures. The students will also acquire competences to implement supervision and inspection systems by using industrial perception technologies and by applying techniques for parameters estimation and patter recognition for advanced signal processing.

After completing this module, the students will face the election between two fields of expertise: automation or supervision.

Module 3: Advanced Automation (9 ECTS Credits)

This module constitutes the nucleus of the Advanced Automation speciality, thus its courses are compulsory for those students pursuing expertise in this field. They will study advanced methodologies and frameworks for the analysis and modelling of complex automated systems, which will include object-oriented techniques among others, as a way to develop higher level and more intuitive solutions.

Safety is a key factor in the development of any automated system. Special attention has to be paid during the design phase in order to take into account all the safety aspects of a machine or a process: functionality, equipment, products, standards, etc.

Module 4: Advanced Supervision (9 ECTS Credits)

This module is the nucleus of the Advanced Supervision speciality, thus its courses are compulsory for those students pursuing expertise in this field. Students will be faced with additional advanced industrial perception and signal processing technologies for the design of industrial inspection and supervision systems.


On the other hand, students will be faced with the study of intelligent techniques for the design of systems for parameters estimation and pattern recognition, for those areas where other no so advanced techniques have proved inefficient. Dimensionality reduction, machine learning, and computational intelligence with special emphasis in neural networks, decision trees, and evolutionary algorithms, are examples of such techniques.

Module 5: Complementary Technologies (9 ECTS Credits)

This module is compulsory for all the students. It is made up of a catalogue of elective courses that allow the students to complement its curriculum with topics of their interest.

Module 6: Internship (12 ECTS Credits)

This module is designed to let the students have a first contact with a professional environment in a real company, allowing them to gain horizontal capabilities like those needed to develop a successful professional career, e.g. team working, maturity, boss-employee relationship, peer to peer relationship, etc.

Module 7: Final dissertation (18 ECTS Credits)

The final dissertation is intended to provide the students with the opportunity to apply the knowledge and capabilities they have acquired during the courses in a hands-on final project.

This project will be carried out along with the internship at the company when possible.


Detailed course descriptions

Industrial Informatic Systems (6 ECTS)

This course will provide industrial engineering or related discipline graduate students with the basic competences to understand and use the necessary ICTs to successfully attend other courses.

Students can exclusively take this course or “Automation and Process Control” course based on their background curriculum.


Basic programming concepts. Programs, data types, expressions and operators, procedures and functions,

Data types. Simple and structured data types, lists, queues, tress.

Algorithmic fundamentals. Iterative and recursive algorithms. Searching and sorting algorithms.


Communication networks fundamentals. ISO/OSI model. Local area networks. TCP/IP.


Automation and Process Control (6 ECTS)

This course will provide those students with a major in computer science or a close related discipline with the basic competences about automation engineering and process control theory subjects, which will allow them to successfully attend other courses.

Students can exclusively take this course or “Industrial Informatics Systems” course based on their background curriculum.


General structure of an automated system, components and functional relations. Organizational architecture of a productive system.

Fundamentals of automation. Wired logic (Electrical technology; Pneumatic Technology, Electronic Technology). Programmed logic (Microcontrollers, PLCs, PCs y digital regulators).

Fundamentals of process control. Systems and signals. Dynamic analysis: time and frecuency domain. Feedback systems. Control structures and regulators tuning.

Computer control. Supervisory control. HMIs & SCADAs.

Analysis and Implementation of Automation Systems

(9 ECTS)

This course will provide the students with the basic capabilities about the use of the most popular analysis methodologies and modelling languages for automated systems, e.g. GEMMA and GRAFCET. They will also study the standard IEC 61131 for programmable logic controllers (PLCs), and will study the main characteristics of commercial distributed control systems.


- Analysis methodologies for automated systems: GEMMA. Analysis techniques: cascade, top-down, bottom-up.

- Modelling Languages. GRAFCET & STATECHARTS.

- Software architecture. Distributed Control Systems. IEC 61499. PCS7, Freelance. - Advance PLC programming. IEC 61131-3.


Industrial Software Development (6 ECTS)

This course will provide the students with the basic capabilities necessary for the analysis, design and implementation of real-time software systems, targeted to the robust design of industrial software applications of average complexity.


- Computer control systems.

- Real-time software systems. Analysis and design methodologies. Implementation. - User interfaces for industrial software. Design constraints. Implementation.

- Software reliability and Exception management.

Industrial Inspection Systems (9 ECTS)

This course will provide the students with the basic capabilities for the design of the entire inspection system for an industrial application, addressing also the interpretation of results both for decision taking and for the subsequent analysis


- Automatic industrial inspection systems: areas of interest and plant integration. - Measurement of geometric features in an inspection system.

- Advanced technologies for industrial inspection: computer vision, 2D image processing, fringe projection, interferometry, thermography, etc. Applications, pros and cons.

- Estimation of process parameters: bayesian and maximum likelihood estimation.

- Pattern recognition: Bayesian classifiers; nonparametric classification techniques (k neighbours, Parzen windows); linear classifiers; introduction to nonlinear classifiers (artificial neural networks, decision trees).

- Machine learning: overfitting; cross validation; boosting y bagging. Nonsupervised learning: clustering.

Advanced Technologies for System Integration (6 ECTS)

At the end of this course the student will be able to evaluate, dimension and plan ahead the horizontal and vertical integration needs for the system and include them as part of the design of the plant automation. In order to fulfil this, the student will be able to select the most suitable integration technologies, design the network architecture, and apply the information technologies to allow remote data to be harnessed effectively.


- Network-based integration.


- Integration of business and production.

Plants and Industrial Processes (6 ECTS)

This course will teach the students the main characteristics of the different types of productive processes by visiting the most representative industries of their kind in the region. The students will be able to analyse and design P&ID diagrams, and to define the basic automation architecture of plant.


- Types of productive processes: pulp & paper, steel, food & diary, manufacturing, chemical, etc. - Plant Layout and Automation Architecture.

- Process and Instrumentation Diagrams (P&ID).

Advanced Methodologies for Automation (3 ECTS)

This course will provide the students with the capability to analysis and design automated systems by means of advanced frameworks, methodologies, and technologies. They will also learn how to apply the object-oriented paradigm to the modelling and programming of PLCs.


- Structured Methodologies: MoWiMa, Machine, STATEMATE, etc. - Object-Oriented Methodologies: UML/UML-RT, etc.


Object-Oriented modelling and programming with the IEC61131 standard.


Process Control Frameworks: TACO/TANGO, EPICS, UNICOS, etc.

Safety in Automation (6 ECTS)

This course will teach the students the basic legislation, regulations, and standards in the field of safety in automation. The students will be able to design safety control systems for industry, machine, and processes.


- Legislation and regulations.

- Functional safety in electric, electronic and programmable control systems. (IEC/EN 61508). - Process industry safety systems (IEC 61511).

- Machine safety control systems (IEC/EN 62061, ISO 13849-Parte 1).


3D Computer Vision (4,5 ECTS)

After completion of this course, the student will be able to analyse the necessary techniques for 3D scene reconstruction from a set of images or a video sequence, as well as to build industrial applications based on 3D information gathering


Part I: 3D reconstruction methods. - Geometric approximations - Photogrammetry

- Shape from focus

- Integration of different cues Parte II: Applications

- Quality inspection in industrial environments - Man-machine interaction

Intelligent Techniques for Industrial Inspection (4,5 ECTS)

This course will enable the student to understand the importance of computational intelligence for industrial inspection systems, to be able to apply dimension reduction techniques to the feature extraction process for complex processes and to apply artificial neural networks, evolutionary techniques and decision trees to parameter and state estimation and to pattern recognition systems for industrial inspection


- Computational intelligence and machine learning. - Dimension reduction techniques: ICA, PCA, etc.


Artificial neural networks. Applications to pattern recognition and estimation.


Evolutive algorithms. Modelling and parameter tunning.


Decision trees.

Home and Building Automation (3 ECTS)

This course will provide the students with the basic capabilities to design and develop home and building automation projects. The students will learn the characteristics of the main technologies and products used to implement home and building automation systems such as KNX-EIB, Lonworks, X10-A10, etc.


- Home and building automation. Definitions. Regulations and legislation. Selection criteria.


- Home and building automation projects commissioning. Phases. Environment analysis and functional requirements specification. Sensors and actuators selection criteria. Hardware and software solution design. Control and HMI programming. Commissioning. Maintenance.

- Case study. Ambient intelligence introduction.

Data Visualization (3 ECTS)

This course will allow the student to understand the possibilities of the data visualization approach as a way to amplify cognition and to gain insight on a scientific and/or technical problem. Besides this, the student will be able to design appropriate graphical representations according to the available information and problem domain knowledge, as well as to the type of information to be displayed. The student will also be able to develop advanced data visualization interfaces, combining graphical elements to encode data such as transparency, colour, size, movement, etc., with interaction mechanisms such as brushing, selection, view reconfiguration, etc.


- Introduction.

- Perception and cognition. - Design principles.

- Data visualization techniques.

- Intelligent data analysis algorithms for data visualization. - Data visualization tools.

State Space Control Systems (3 ECTS)

This course is oriented to acquire knowledge on control-oriented modeling of industrial systems. It comprises mathematical formulation of multivariate linear systems, computer-based simulation and control design. Final goal is to set rigorous basis for the design of computer controlled complex industrial systems.


- Preface. Contents and Introduction.

- Modelling and simulation of industrial systems: concepts , multivariate models , methodologies , examples.

- Dynamic behaviour. Solution of differential equations, Qualitative Analysis , Stability, Lyapunov stability , parametric nonlocal response .

- Linear Systems : Basic definitions , Exponential Matrix response , linearization - State Feedback of: Reachability , Stability, Integral Action.

- Output Feedback : Observability , State Estimation , Kalman Filtering , - Transfer Functions for multivariate systems: Analysis in the frequency domain .

- PID Control: Control Functions , Simple controllers for complex systems , tuning PID (Ziegler


Embedded Systems (3 ECTS)

This course will allow the student to understand the basis of embedded systems design and their working principles. He will be able to design an embedded system aimed to solve a precise problem, paying particular attention to the selection of the most suitable hardware to fulfil the requirements, and to implement a prototype for a given application with special focus on fault tolerance and system reliability.


- Microprocessors, microcontrollers, and Digital Signal Processors. - Embedded systems principles design.

- Development environments for embedded systems. - Operative systems and real-time core.

- Safety, reliability, and fault tolerance. - Embedded systems test and validation.

Virtual Instrumentation (3 ECTS)

This course will allow the student understanding the operation and application fields of the virtual instrumentation discipline. He will be able to design and implement a virtual instrumentation application using specific software.


- General concepts and application fields.

- Basic architecture of a virtual instrumentation system.

- Languages and environments oriented to virtual instrumentation: LabView, LabWindows, Matlab/Simulink, DASYLab.

Digital Signal Processing (3 ECTS)

This course will provide the student with the basic capabilities to understand the foundations of the main digital signal processing techniques, and to design different signal filters. The Fourier transform is studied from an engineering point of view. Analogue and digital filter properties are compared, and different design approaches are studied.


- The breadth of DSP. - ADC and DAC .

- Linear systems and convolution. Kernel filters. - The discrete Fourier transform and its applications. - Multiresolution signal analysis.


Intelligent Manufacturing Systems (3 ECTS)

This course will teach the student the basic properties and applied standards to the intelligent manufacturing systems (IMS), including the holonic systems. The students will be able to analyse and design discrete, continuous, and batch manufacturing systems by reuse of modular designs, and to know the importance of the evolution from proprietary to open distributed manufacturing systems.


- IMS basis.

- Standards and regulations for the design, use, and maintenance of IMS.

- IT technology for the commissioning of collaborative manufacturing systems: virtual reality, agents, sensorization, no hierarchical networks, RFID, etc.

- Hardware components to implement IMS.

- Holonic systems. Basic principles: autonomy, cooperation, and automatic reconfiguration. Case


Business Management Systems Information (3 ECTS)

This course will teach the students the structure of the IT infrastructure of an industry, and will teach them to design a production management system, e.g. data bases, business layer, user interface, etc. The students will also learn how to vertically integrate the production management system with the process control and data acquisition systems.


- IT infrastructure in industry.

- Production management introduction. MES (Manufacturing Execution System).

- Relevant information for production systems: lots, raw material, inputs, human resources, recipes, etc. (Documentary management system).

- Costing calculation methods: standard price, variable price, real price. Costs deviations calculation and allocation.

- Cost centres. Accounting counts. Crossed information.

- Process lines and machines efficiency. OEE (Overall Equipment Efficiency).

- GIS (General Information System). Information cubes. Dynamic tables. Balance score card. - Interface with SAP. Methods to extract information.

- Computer-aided maintenance management (CAMM). Maintenance plans and programs. Components definition (machines, lines, spare parts, etc).


Specific Research Aspects (3 ECTS)

This course will provide the student with the basic capabilities for the scientific research in engineering, as well as knowing the search engines: data bases, thematic portals, and R&D finance resources. The student will be able to write a scientific paper using the analysis, synthesis, and exposition techniques inherent to the technical writing.


- Scientific research methodology in engineering.

- Ethic implications in scientific research. ¿Plagiarism or reference?

- Resource search: Data bases (ISI...), thematic portals (IEEEXplore), R&D Finance sources. - Scientific paper writing in engineering. Writing, Software tools.

- Research results publishing.

- Public and private R&D finance search.

Energy Efficiency in Industry (3 ECTS)

This course will allow the students to know general aspects about energy efficiency in industry, e.g. legislation, international standards, best practices, etc. The students will be able to design and apply different types of energy measurement systems in industry, and will get to know and objectively evaluate the importance of the quality, reliability, and availability of energy to apply such criteria to the design of solutions.


- Introduction. Basic energy legislation and regulations. Phases to commissioning energy efficient systems in industry.

- Energy diagnosis. Sources of energy. Types of energy in industry. Main consumptions of energy in industrial processes. Data acquisition and energy measurement in industrial processes. Applying automation and industrial informatics to implement energy measurement systems.

- Energy analysis. Potential savings estimation. Integration of improvement measures. Technical viability and return of investment. Energy bill optimization.

- Commissioning of energy efficiency measures. Continues monitoring and system sustainability. Energy quality, reliability, and availability.

- Case study. Equipment and systems. Conclusions.

Internship and Final Dissertation (30 ECTS)

The third semester is fully devoted to carry out an internship at a company and to develop the final dissertation.






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