Sustainable Industry
Study programme title in Est.
Jätkusuutlik tööstus
Study programme title in Engl.
Sustainable Industry
TalTech study programme code
RATM24
MER study programme code
251464
Study programme version code
RATM24/25
Faculty / college
E - School of Engineering
Head of study programme/study programme manager
Olga Dunajeva
Language of instruction
Estonian
Study level
Master study
ECTS credits
120
Self-paid study programme
no
Nominal study period
4 semesters
Study programme group
Engineering, Manufacturing and Technology
Broad area of study
Engineering, Manufacturing and Construction
Study field
Engineering and engineering trades
Curriculum group
Engineering and engineering trades not elsewhere classified
Access conditions
The condition for starting a master's program is a bachelor's degree in engineering or IT fields (incl. applied higher education). Exceptionally,
bachelor's degrees in other disciplines are also accepted. According to admission regulations of TalTech.
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Study programme aims and objectives
The objective of the curriculum is to train:
- specialists

in industrial digitization with an engineering background who are capable of planning and executing automation or robotics projects, selecting and configuring automation tools or robotic systems, and focusing on the specific requirements of the industry;
- professionals prepared to support the transition to a green economy through the rational implementation, analysis, and synthesis of modern circular economy systems, and the use of relevant production management and production system design methods.

An additional goal of the curriculum is retraining and continuing education, incl. workplace-based learning, for professionals with higher education already active in the workforce, significantly enhancing their value in the labor market.

Upon completing the curriculum, the graduate acquires specialized skills in management, development, automation, and robotics. The studies shape a specialist with digital skills that promote the industry and a worldview based on the circular economy.
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Learning outcomes of the study programme
Upon completing the curriculum, the graduate:
- analyzes, evaluates,

and classifies broad-based knowledge of Industry 4.0 concepts, theories, research methods, and trends, able to generate new techniques and approaches for their implementation;
- identifies, formulates, and generates new ideas and interdisciplinary connections for the application of circular economy solutions in related fields;
- proposes solutions for the development of the concept of digital manufacturing;
- selects, justifies, and uses appropriate methods and technologies for solving professional tasks, models and/or assesses possible consequences;
- constructs knowledge about entrepreneurship, innovation, and creative problem-solving;
- applies and combines IT tools and solutions in solving complex engineering tasks and practical problems;
- uses modern modeling, simulation, analysis, and synthesis techniques;
- applies data analysis and data mining skills to optimize industrial processes and other tasks, combining acquired knowledge with practical teamwork and communication and interpersonal skills.
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Graduation requirements
Completing the curriculum in the required volume and defending the thesis according to the regulations established by the TalTech Senate; to obtain a cum laude diploma,
the thesis must be defended with a grade of '5' and the weighted average must be at least 4.60, taking into account all grades listed on the academic transcript.
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Degrees conferred
Master of Science in Engineering
Study programme version structure :
Module type
total ECTS credits
General studies
12.0
Core studies
21.0
Special studies
48.0
Free choice courses
18.0
Graduation thesis
21.0
Total
120.0
  • +
       MAIN SPECIALITY 1: Sustainable Industry
    • +
         MODULE: General Studies 12.0 ECTS credits (General studies)
      Aims
      The general education module focuses on essential areas in business and research,
      preparing students for versatile and informed engagement in the worlds of entrepreneurship and research. Students gain knowledge in business process management, entrepreneurial principles, and academic writing skills. Additionally, they acquire an understanding of intellectual property protection and research methodologies. The module introduces principles of circular economy, business models, associated policies, and legislation.
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      Learning outcomes
      After completing this module, the student:
      - has comprehensive knowledge of company business processes, their management, and development;


      - has acquired essential skills in process management and can successfully apply them in the management of technological processes;
      - has mastered the basics of academic writing and gained initial knowledge of intellectual property protection and research methodologies;
      - knows the principles and legislation of the circular economy.
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      Elective courses:
      Course title
      Course code
      ECTS credits
      Hours per week
      Lectures
      Practices
      Exercises
      E/P-F.Ass./ Gr.Ass.
      Teaching semester
      Introduction to the Circular Economy
      EKX0020
      3.0
      2.0
      1.9
      0.0
      0.1
      E
      S
      Business Activity and Enterprise Economy
      EVM0010
      6.0
      4.0
      2.0
      0.0
      2.0
      E
      SK
      Fundamentals of Scientific Reasearch and Academic Self-Expression
      EVM0020
      6.0
      4.0
      2.0
      1.0
      1.0
      A
      SK
      Advanced Academic English
      EVM0420
      6.0
      4.0
      0.0
      4.0
      0.0
      A
      SK
      Strategic Managerial Accounting and Cost Management
      MMA5070
      6.0
      4.0
      2.0
      0.0
      2.0
      E
      S
      Business Process Management
      MMK5270
      6.0
      3.0
      1.0
      0.0
      2.0
      E
      S
      Intellectual property and innovation
      RAH0840
      3.0
      2.0
      1.5
      0.0
      0.5
      A
      SK
      Total: at least 12.0 ECTS credits
    • +
         MODULE: Core Studies 21.0 ECTS credits (Core studies)
      Aims
      The main objective of the basic education module is to provide in-depth knowledge of data processing,
      analysis, visualization, as well as methods of machine learning and data mining, essential for contemporary industry. It aims to give an overview of process modeling and computer simulation in various fields, including industrial technology and materials engineering, emphasizing their practical application. It is crucial to acquire the necessary skills in the control methods of automation objects and the construction of HMI (Human-Machine Interface) systems, which are decisive in industrial processes. The module also aims to provide practical experience in solving quality assurance tasks, helping students understand and implement quality management systems, certification, models, methods, and standards.
      Furthermore, the module aims to develop students' ability to select and use appropriate methods and technologies for solving professional tasks and to strengthen their project and teamwork skills.
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      Learning outcomes
      After completing this module, the student:
      - selects suitable methods for visualizing and analyzing industrial data, and can assess and interpret the results of data analysis;


      - is familiar with the latest trends and standards in Human-Machine Interface (HMI) and can apply them in the creation of HMI systems, ensuring a better user experience and efficiency;
      - has knowledge of commonly used data communication standards and the principles of protocols, enabling them to identify the most suitable data communication solution for a specific industrial application, ensuring smooth data exchange;
      - is adept at implementing quality management methods in the planning, execution, and analysis of processes in the industry;
      - possesses strong project and teamwork skills, facilitating effective collaboration and contribution to teams and projects.
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      Compulsory courses:
      Course title
      Course code
      ECTS credits
      Hours per week
      Lectures
      Practices
      Exercises
      E/P-F.Ass./ Gr.Ass.
      Teaching semester
      Analysis and Visualization of Industrial Data
      EVM0370
      9.0
      6.0
      2.0
      4.0
      0.0
      E
      SK
      Total: 9.0 ECTS credits
      Elective courses:
      Course title
      Course code
      ECTS credits
      Hours per week
      Lectures
      Practices
      Exercises
      E/P-F.Ass./ Gr.Ass.
      Teaching semester
      Quality Management in Industry
      EVM0290
      6.0
      4.0
      2.0
      0.0
      2.0
      H
      SK
      Process Modelling
      EVM0350
      6.0
      4.0
      2.0
      0.0
      2.0
      H
      SK
      Human-Machine Interface and Web Technology in Automation
      EVM0380
      6.0
      4.0
      1.0
      3.0
      0.0
      H
      SK
      Data Communication Technologies and Applications
      EVM0490
      6.0
      4.0
      2.0
      2.0
      0.0
      H
      SK
      Foundations of Programming
      RAR2770
      6.0
      4.0
      2.0
      2.0
      0.0
      H
      SK
      Total: at least 12.0 ECTS credits
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         MODULE: Sustainable Industry 48.0 ECTS credits (Special studies)
      Aims
      The main objective of the module is to provide a systematic overview and comprehensive knowledge of sustainable industrial processes and their management.
      The module imparts knowledge on planning and implementing projects related to robotics, automation, and digitalization. It covers topics such as creating process flows, virtual representation, displaying Key Performance Indicators (KPIs) on a digital dashboard to analyze and monitor production performance, and enhance productivity.
      The module also focuses on the implementation of integrated energy systems to reduce resource usage, increase energy efficiency, and digitize technology. Additionally, students are prepared for topics related to classical artificial intelligence, robotics, and circular economy systems, as well as for the preparation and defense of master's theses.
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      Learning outcomes
      After completing this module, the student:
      - recognizes and establishes interdisciplinary connections that enable effective problem-solving and innovation;


      - possesses knowledge of and can use hardware and software tools for production automation, industrial data communication systems, and standards;
      - is familiar with techniques and methods of machine vision and can apply them in various technical systems, such as robotic systems and production lines;
      - is proficient in creating virtual environments and simulations for industrial processes, utilizing Extended Reality (XR) possibilities. This expertise supports the optimization of processes and fosters innovation.
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      Compulsory courses:
      Course title
      Course code
      ECTS credits
      Hours per week
      Lectures
      Practices
      Exercises
      E/P-F.Ass./ Gr.Ass.
      Teaching semester
      Production Digitalization
      EMT0160
      6.0
      4.0
      1.0
      3.0
      0.0
      E
      SK
      Master`s Seminar
      EVM0210
      6.0
      2.0
      1.0
      0.0
      1.0
      A
      SK
      Foundations of Human-Robot Interaction
      EVM0360
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      SK
      Cybersecurity and Sustainability
      EVM0390
      6.0
      4.0
      2.0
      0.0
      2.0
      E
      SK
      Total: 24.0 ECTS credits
      Elective courses:
      Course title
      Course code
      ECTS credits
      Hours per week
      Lectures
      Practices
      Exercises
      E/P-F.Ass./ Gr.Ass.
      Teaching semester
      Project Management
      EVM0060
      6.0
      4.0
      2.0
      0.0
      2.0
      E
      SK
      Smart Systems Design
      EVM0220
      6.0
      4.0
      2.0
      2.0
      0.0
      H
      SK
      Integrated Energy Systems and Smart Grids
      EVM0310
      6.0
      4.0
      3.0
      1.0
      0.0
      A
      SK
      Robot-Based Solutions in Manufacturing
      EVM0460
      6.0
      4.0
      1.0
      3.0
      0.0
      H
      SK
      Automation and Control Theory
      EVM0470
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      SK
      PLC Programming
      EVM0480
      6.0
      4.0
      2.0
      2.0
      0.0
      H
      SK
      Computer Vision and Visual Intelligence
      EVM0500
      6.0
      4.0
      2.0
      2.0
      0.0
      H
      SK
      Database Systems Technologies
      EVM0510
      6.0
      4.0
      2.0
      2.0
      0.0
      E
      SK
      Data Mining and Big Data Applications
      EVM0520
      6.0
      4.0
      2.0
      2.0
      0.0
      H
      SK
      Problem and Project Based Learning
      UTT0120
      6.0
      4.0
      0.0
      4.0
      0.0
      A
      SK
      Total: at least 24.0 ECTS credits
    • +
         MODULE: Free choice courses 18.0 ECTS credits (Free choice courses)
      Aims
      The aim of this module is to provide the student a possibility
      to broaden the mind according to their interests and personal qualities by selecting courses from different curricula from home university as well as from universities abroad.
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      Learning outcomes
      Student has improved their knowledge and broadened the mind according to their interests and personal qualities.
    • +
         MODULE: Master thesis 21.0 ECTS credits (Graduation thesis)
      Aims
      The aim of the Master thesis is to deepen the knowledge and
      practical skills of the student through solving the technological or scientific problems in the field of sustainable industry. To prepare the student for independent research and development work in the field.
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      Learning outcomes
      After completing this module, the student:
      - has acquired profound

      knowledge and practical skills for solving technological or scientific problems in the field of green energy technologies;
      - is able to choose and use suitable methods and collect as well as critically analyse relevant information for solving a research and development problem;
      - can present the results of their work in written and oral form as well as discuss the content of the work;
      - is prepared for independent research and development work in the field or for continuing studies at a doctoral level.
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         STANDARD STUDY PLAN: Autumn daytime study
      • +
           1st Semester
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           2nd Semester
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           3rd Semester
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           4th Semester
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           0 Semester
    • +
         STANDARD STUDY PLAN: Autumn session-based study
      • +
           1st Semester
      • +
           2nd Semester
      • +
           3rd Semester
      • +
           4th Semester