Course content

• Industry 4.0
• Industrial internet-of-things
• Sensor technology
• Data mining and big data analysis
• Digital twin
• Security in industry 4.0

Learning outcome

After completing the course, students will have advanced knowledge on industrial communications and sensor technology, data mining and big data analysis for manufacturing systems, and security aspects of Industry 4.0. Knowledge: -Thorough knowledge on the different capabilities of industrial internet-of-things for sustainability and strategy -Advanced knowledge on the different industrial communication systems and sensor technologies -Advanced knowledge on the use of data mining and big data analysis for industrial applications - Advanced knowledge on the concept of digital twin in manufacturing systems -Thorough knowledge and understanding on the security aspects of Industry 4.0. Skills: -Can analyze the possibilities as well as challenges of deploying sensors and communication systems in industrial use-case scenarios -Can carry out an independent and limited research on system design of industrial communication systems General competence: - Understand the different automation capabilities using industrial internet-of-things and sensor technology - Understand the application of data mining and big data analysis in industrial use-case scenarios - Understand the concept of digital twin in manufacturing systems - Understand the security threats of Industry 4.0 - Can contribute to new thinking and innovation in the area of industrial communications and sensor technology -Can apply his/her knowledge and skills in new areas in order to carry out advanced assignments and projects within industrial communication and sensor technology

Learning methods and activities

The course is seminar based and the teaching language is English. Handout research papers and/or reports will be utilized to cover the course topics. Each student (or a student group) will study the assigned papers/reports and prepare a presentation to the class. The quality of the seminar will count for 20% of the final grade. The seminars in the course will be given on campus, and are open for both categories of students (campus- and remote students) through a web conference-system. All students (campus and remote) are required to contribute to at least one seminar with a presentation. The oral examination at the end of the course (which will count for the rest 80% of the final grade) will be based on the contents of all the seminars.

Compulsory assignments

• Contribution to a seminar

Further on evaluation

The students will prepare a presentation on a chosen topic that they will present to the class for 45 minutes. Topics are chosen in collaboration with the lecturer. This counts 20% of the final grade. Oral examination at the end of the semester will count for 80% of the final grade. Re-sit examination: New oral examination in August

Specific conditions

Recommended previous knowledge

The course is open for students with background in manufacturing or electrical engineering.

Required previous knowledge

It is suggested that the students have some basic knowledge in the field of data communications. Otherwise, a crash course (introduction) on data communications will be provided at the beginning of the course.

Course materials

Handout research papers (articles) and/or reports

Credit reductions