Robotics
| Structure Type: | Study unit |
|---|---|
| Code: | IKA0405 |
| Curriculum: | KT 2022 |
| Level: | Bachelor of Engineering |
| Year of Study: | 2 (2023-2024) |
| Semester: | Spring |
| Credits: | 5 cr |
| Responsible Teacher: | Billing, Mika |
| Language of Instruction: | Finnish |
Courses During the Academic Year 2023-2024
| Impl. | Group(s) | Study Time | Teacher(s) | Language | Enrolment |
|---|---|---|---|---|---|
| 3007 | KT2022-2A, KT2022-2B, KT2022-2C, KT2022-2D | 2024-01-08 – 2024-04-28 | Sami Elomaa | Finnish | 2023-12-01 – 2024-01-12 |
| 3008 | KT2021V-3A, KT2021V-3B | 2023-08-25 – 2023-12-17 | Sami Elomaa | Finnish | 2023-08-01 – 2023-09-06 |
Learning Outcomes
The student will learn about the efficient and safe use and programming of industrial robots.
Student's Workload
Total work load of the course: 135 h
- of which scheduled studies: 60 h
- of which autonomous studies: 75 h
The assessment of student’s own learning 1 h is included in contact lessons.
Prerequisites / Recommended Optional Courses
IKA0404 Machine Automation
Contents
The implementation and construction of industrial robots, safety, applications and external devices; programming and simulation.
Recommended or Required Reading and Other Learning Resources/Tools
Suomen Robotiikkayhdistys. Robotiikka, Talentum.
Mode of Delivery / Planned Learning Activities and Teaching Methods
Lectures and exercises.
Assessment Criteria
5: The student is able to utilise the methods learnt during the study unit independently and is able apply the learnt knowledge in new contexts.
3: The student is able to utilise the methods learnt during the study unit independently.
1: The student is able, with guidance, to utilise the methods learnt during the study unit.
Assessment Methods
Examination, laboratory exercises.