Industrial Robotics (3 cr)
Code: TSAR0530-3007
General information
Enrollment
01.11.2024 - 09.01.2025
Timing
13.01.2025 - 18.05.2025
Number of ECTS credits allocated
3 op
Mode of delivery
Face-to-face
Unit
School of Technology
Campus
Lutakko Campus
Teaching languages
- English
Seats
20 - 35
Degree programmes
- Bachelor's Degree Programme in Electrical and Automation Engineering
Teachers
- Samppa Alanen
Groups
-
TAR22S1Bachelor's Degree Programme in Automation and Robotics
- 13.01.2025 13:15 - 14:45, Industrial Robotics TSAR0530-3007
- 20.01.2025 13:15 - 14:45, Industrial Robotics TSAR0530-3007
- 27.01.2025 13:15 - 14:45, Industrial Robotics TSAR0530-3007
- 03.02.2025 13:15 - 14:45, Industrial Robotics TSAR0530-3007
- 10.02.2025 13:15 - 14:45, Industrial Robotics TSAR0530-3007
- 17.02.2025 13:15 - 14:45, Industrial Robotics TSAR0530-3007
- 04.03.2025 09:00 - 10:30, Industrial Robotics TSAR0530-3007
- 11.03.2025 09:00 - 10:30, Industrial Robotics TSAR0530-3007
- 18.03.2025 09:00 - 10:30, Industrial Robotics TSAR0530-3007
- 25.03.2025 09:00 - 10:30, Industrial Robotics TSAR0530-3007
- 01.04.2025 09:00 - 10:30, Industrial Robotics TSAR0530-3007
- 08.04.2025 09:00 - 10:30, Industrial Robotics TSAR0530-3007
- 15.04.2025 09:00 - 10:30, Industrial Robotics TSAR0530-3007
- 22.04.2025 09:00 - 10:30, Industrial Robotics TSAR0530-3007
- 29.04.2025 09:00 - 10:30, Industrial Robotics TSAR0530-3007
Objective
Main objective for this course is acquiring knowledge in industrial robotics. Studying in this course require knowledge in fundamentals of technology and programming skills. This course enables further studies of the subject in other courses.
EUR-ACE APPLYING TECHNOLOGY INTO PRACTICE
Student is familiar with the structures and applications of industrial robots as well as programming methods. Student is able to design a robot into part of production cell.
Content
Industrial robots, structures, applications
Designing robot cell
Programming robots
Oppimateriaali ja suositeltava kirjallisuus
Materials in the e-learning environment.
Teaching methods
- independent study
- distance learning and remote lectures
- webinars
- small group learning
- learning tasks
Exam schedules
The possible date and method of the exam will be announced in the course opening.
Vaihtoehtoiset suoritustavat
The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.
Student workload
One credit (1 Cr) corresponds to an average of 27 hours of work.
- lectures 30h
- assignments; group and independent study 51h
Total 81h
Further information
The evaluation is based on the qualitative evaluation of the exam and exercises/assignments.
Evaluation scale
0-5
Arviointikriteerit, tyydyttävä (1-2)
Sufficient (1): Student recognizes the basics and terminology, but has shortcomings in understanding the key issues.
Satisfactory (2): Student knows the basics and terminology, but has shortcomings in the application of key issues.
Arviointikriteerit, hyvä (3-4)
Good (3): Student is able to apply the basics in practice.
Very good (4): Student knows the key subjects and is able to apply them in different implementations.
Assessment criteria, excellent (5)
Excellent (5): Student masters key subjects and is able to apply them creatively and innovatively.
Qualifications
Fundamentals in technology, programming skills