Digital Manufacturing (DM)

Degree:
Digital Manufacturing (DM)

ECTS:
120 ECTS

Field of Study:
Computer Science and Information Technology

Duration:
2 years, full-time

Eligibility:
Hold a Bachelor of Science or be in the final year of studies of... (read more).

Tuition fees & scholarships:
For EU and non-EU citizens.
More information.

Language of Instruction:
English
More information.

Digital Manufacturing (DM)

Why study Digital Manufacturing at EIT Digital Master School?

This Digital Manufacturing (DM) Master Program could be considered aligned with other initiatives at National and International level to develop and promote the implementation of digitalization technologies in EU industry, that could lead to an increase of productivity on every sector. A key factor on this process is going to be the engineering profile of the people that will lead this transformation, a real integrated curriculum among Industrial and Manufacturing technologies, together with computer science and telecommunications technologies. The aim of this Program is to provide this truly integrated curriculum on student.

The EIT Digital Master’s degree DM is an interdisciplinary program that combines generation and predictive use of data arising from the Industrial Assets, and the Computer Science tools to develop Decision Making and Artificial Intelligence for Industry.

Who can apply?

If you wish to apply to this program you must have a Bachelor of Science in, or be in your final year of studies of:

  • Computer Science 
  • Mathematics
  • Statistics
  • Electrical Engineering
  • Mechanical Engineering 

In special cases students from Industrial Engineering, Chemical Engineering can be considered.

How is the programme structured?

All EIT Digital Master School programmes follow the same scheme:

  • Students study one year at an ‘entry’ university and one year at an ‘exit’ university in two of EIT Digital’s hot spots around Europe.
  • Upon completion, graduates receive degrees from the two universities and a certificate awarded by the European Institute of Innovation and Technology.
  • The first year is similar at all entry points with basic courses to lay the foundation for the chosen technical programme focus. Some elective courses may also be chosen. At the same time, students are introduced to business and management. During the second semester, a design project is combined with business development exercises. These teach how to turn technology into business and how to present a convincing business plan.
  • In between the first year and the second year, a summer school addresses business opportunities within a socially relevant theme.
  • The second year offers a specialisation and a graduation project. The gradation project includes an internship at a company or a research institute and results in a Master thesis with a strong innovation and entrepreneurship dimension.

To learn more about the I&E minor please click here.

Where can I study Digital Manufacturing?

Entry 1st Year

  • Technical University of Madrid, Spain

Exit 2nd Year

  • Eötvös Lorand University (ELTE), Hungary
  • Tallinn University of Technology, Estonia
  • University of Turku, Finland

What can I study at the entry and exit points?

Entry - 1st year, common courses

Entry university in Digital Manufacturing provides introductory courses, from Mechanical-Manufacturing, Advanced Robotics, Industrial Internet of the Things, Artificial Intelligence and Operation Technologies Cybersecurity Areas. These Areas are considered the core knowledge to develop the Factory of the Future on every industrial business.

Technical University of Madrid ETSII-UPM, Spain

Link to the university: www.etsii.upm.es
Programme
Contact: Dr. Juan J. Marquez; juandejuanes.marquez@upm.es

LIST OF COURSES:

Compulsory common (36 ECTS), I&E (20 ECTS)

First Semester

  • Introduction to digital factory (1 ECTS)
  • Programming for factory engineers / factory engineering for programmers (6 ECTS)
  • Advanced robotics (6 ECTS)
  • Industrial internet of the things (6 ECTS)
  • Introduction to innovation and entrepreneurship management (6 ECTS)

Second Semester

  • Digital manufacturing (8 ECTS)
  • Artificial intelligence (8 ECTS)
  • Operation technologies cybersecurity (1 ECTS)
  • Introduction to technology watch and competitive intelligence (1 ECTS)
  • I&e seminars (5 ECTS)
  • Entrepreneurship and business modelling (6 ECTS)
  • Launching of ict product/services to the market (2 ECTS)

Summer Course

  • 4 ECTS Summer Courses on Innovation & Entrepreneurship

COURSE DESCRIPTION

Factory Engineering for Programmers/ Programming for Factory Engineers

This is an elective oriented to nivelation of Computer Science Engineering or equivalent tracks on Factory Engineering Knowledge (Industrial/Manufacturing), and Mechanical/Electrical/Industrial to programming background for Digital Factory Applications

Advanced Robotics

This subject is focused on applying robotics arm manipulation and mobile platforms technologies to industrial processes. Applied robotics discusses topics related to mobile robotics (ground, aerial and water-underwater) vehicles, complex arm manipulation, and robotic software programming platforms, such as ROS and several simulation and designing tools.

Industrial Internet of the Things

The aim of this subject s to cover basic aspECTS of communication networks, and how to implement them from the point of view of the design of embedded systems on the edge.Communication networks, wireless technologies and others, Embeded computing platforms, Embeded operating systems, Real Time Embeded systems

Digital Manufacturing

This course is oriented to develop the basic knowledge on technologies like Product Lifecycle Management systems and Manufacturing Execution Systems, in order to produce valid Product and Production Digital Twin viable to improve productivity and efficiency in real applications, Plant Simulation Technologies will support optimization of the assets and also will allow gathering data to produce other advanced uses and applications

Artificial Intelligence

The main objective of this course is the student to be able to apply the most important Machine Learning Techniques based on Artificial Neural Networks and be able to analyze their results and methodology when compare to classical statistical methods. The methodology is based on solving problems using actual data, some of them based on synthetic data, useful for getting familiar with the techniques, and some others based on data from real-word applications. During the course, we will go through Supervised and Unsupervised Neural Networks, culminating in Deep Learning Methods.

Exit - 2nd year, specialisation

Tallinn University of Technology (TalTech), Estonia

Link to the university: https://www.ttu.ee/en

Specialisation: Smart Solutions for Digital Factories

Innovation and Entrepreneurship module

In this module the concepts related to entrepreneurship, R&D, and innovation are discussed during the course and students apply the obtained skills in the group work assignments.

  • I&E Study (6 ECTS)

24 ECTS Specialization elective courses: 

(combined from the following modules)

Cyber Security

Principles of cyber security and cryptography are discussed. Also, the courses focus on how to protect data when storing and communicating and how to ensure data integrity.

  • Foundations of Cyber Security (6 ECTS)
  • Cryptography (6 ECTS)
  • Cyber Security Management (6 ECTS)

Artificial Intelligence

The courses cover a range of advanced topics in artificial intelligence. The topics and methodologies covered in these courses are used for complex identification and control system.

  • Intelligent Control Systems (6 ECTS)
  • Computer Vision (6 ECTS)
  • Machine Vision (6 ECTS)

Data Management

The courses give a deeper insight into the means and methods to gather, transfer, and analyse data depending on energy, integrity, security, and other relevant requirements.

  • Data Mining (6 ECTS)
  • Data Acquisition Means and Methods (6 ECTS)
  • Applied Data Communication (6 ECTS)

Embedded Systems and IoT

In the final module, the computation and communication using distributed embedded systems are discussed. An additional focus on the concept of Internet-of-Things for industry is analysed and looked into.

  • Basics of Embedded Systems (6 ECTS)
  • Internet of Things for Industry (6 ECTS)
  • Networks of Smart Things (6 ECTS)

University of Turku (UTU), Finland

Specialisation: Data Analytics at the Edge

University website: https://www.utu.fi/en

UTU provides an exit year specialization on real-time sensor data analytics in the digital factory/manufacturing context. It will include a large industry-driven capstone project (multidisciplinary group work) as a recommended elective course with shipbuilding or another relevant branch of manufacturing as a focus area. Turku is well known especially for its thriving shipbuilding and marine engineering industry. 

COURSES

Innovation & Entrepreneurship Study (6 ECTS)

Specialization elective courses (select 25 ECTS from the following list): 

  • Capstone Project (10 ECTS)
  • Data Analysis and Knowledge Discovery (5 ECTS)
  • Applications of Data Analysis (5 ECTS)
  • Machine Learning and Pattern Recognition (5 ECTS)
  • Data Acquisition, Analysis and Visualization Systems (5 ECTS)
  • Autonomous Systems Architectures (5 ECTS)
  • Smart Systems Applications (5 ECTS)
  • Robotic and Autonomous Systems: Interfacing and Sensing (5 ECTS)
  • Mixed Reality (5 ECTS)
  • Firewall & IPS Technology (5 ECTS)
  • Communication Technology and Security in IoT (5 ECTS)
  • Secure Sensor Networks (5 ECTS)

Master’s Thesis (30 ECTS)

Eötvös Loránd University (ELTE), Hungary

Link to the university: www.elte.hu
Contact: Dr. Matyas Ando; am@inf.elte.hu

Specialisation: Communications and Optimization in Digital Manufacturing

The ELTE Faculty of Informatics has great competence both in computer science and in mechanical engineering. Courses within the Digital Factory programme will be supported by hands-on experiences with CNC machines, PLC controlled assembly lines, as well as robots. Thanks to our core infrastructure, we are able to teach Industry 4.0 on a project-oriented basis. In particular, we focus on communication channels and data-driven optimization. Detailed information on infrastructure is available here: http://smi.inf.elte.hu/english/introduction/.

Technical major (24 ECTS):

Digital Manufacturing Lab I. II. (5+5 ECTS): Personalized project task – taking into account prequalification and interest. The project task is related to the machining processes (CNC systems) or assembly line (PLC, Robot), where the data collection and processing is essential. The aim is that students meet with industrial problems and create appropriate solution for it with the help of the supervisor.

Industrial communications (5 ETCS): The subject will focus on the different communication protocols used in industrial environments (UART, IIC, SPI, 1. RS232, RS485, CAN-bus, LIN-bus, FlexRay, MOST, Byteflight, Intellibus, EtherCAT, ProfiBUS, ProfiNET, S7, OPC-UA,WiFi , BlueTooth, Zigbee, LoRa WAN, 433MHz, 868MHz , 3-5G). During the lectures the students will learn about the protocols, their architecture, possible topologies, advantages and shortcomings of these communication methods and when to apply witch one. During these practical lessons the students learn not only how to create such systems, but also how to do debugging in the physical layer.

Data mining (5 ECTS): This course helps student to acquire a deep understanding on the most important fields and algorithms of data mining. The concerned topics are data mining basics, knowledge discovery process, data preparation and data cleaning, similarity and diversity metrics, curse of dimensionality and dimensionality reduction, cluster analysis, classification, frequent itemset mining, association rules and anomaly detection. In order to achieve a deep insight, the course material also provides practical examples with data acquired from various sources.

Elective courses (4 ECTS)

Innovation and Entrepreneurship major (6 ECTS):

I&E Study (6 ECTS): Applying, synthesizing, and evaluating prior innovation and entrepreneurship learning in the context of a specific technology. The course provides differentiated professional skills to the accomplishment of the innovation and entrepreneurship study (I&E study) related to the technical thesis. The course aims the preperation of an I&E study which analizes the business opportunities of the described idea or business process. The teacher evaluates the study.

Master thesis project (30 ECTS)

The first semester studies will be located at the ELTE Savaria Campus in Szombathely, while the internship opportunity of the second semester, based on which the thesis will be grounded, will be in Budapest or Szombathely at an Industry 4.0 partner. During this period students can actively be part of the Budapest Co-location Centre community, having their base and extra curriculum activities here. 

Period 1 Application Deadline: February 3

Have questions? We are here to help!

Degree:
Digital Manufacturing (DM)
ECTS:
120 ECTS
Field of Study:
Computer Science and Information Technology
Duration:
2 years, full-time
Eligibility:
Hold a Backelor of Science or be in the final year of studies of... (read more).
Tuition fees & scholarships:
For EU and non-EU citizens.
More information.
Language of Instruction:
English
More information.

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