Automation Systems
| Structure Type: | Study unit |
|---|---|
| Code: | IKTS2213 |
| Type: | Optional obligatory / Professional Studies |
| Curriculum: | KT 2016 / 2016V / 2017 / 2021 / 2021V / 2022 / 2023 / 2023V / 2024 / 2025 / 2025V |
| Level: | Bachelor of Engineering |
| Year of Study: | 3 / 4 (2018-2019 / 2019-2020 / 2023-2024 / 2024-2025 / 2025-2026 / 2026-2027 / 2027-2028) |
| Credits: | 5 cr |
| Responsible Teacher: | Rantasalo, Marko / Pölönen, Juho |
| Language of Instruction: | Finnish |
Courses
| Impl. | Group(s) | Study Time | Teacher(s) | Language | Enrolment |
|---|---|---|---|---|---|
| 1 | I-KT-3N | 2018-01-08 – 2018-02-23 | Marko Rantasalo | Finnish | 2017-12-11 – 2018-01-15 |
| 2 | I-KT-3N | 2018-08-31 – 2018-12-21 | Marko Rantasalo | Finnish | 2018-08-20 – 2018-09-17 |
| 3 | I-KT-3N | 2020-01-07 – 2020-04-24 | Sami Elomaa | Finnish | 2019-12-16 – 2020-01-14 |
| 4 | I-KT-4V | 2019-09-02 – 2019-12-20 | Marko Rantasalo | Finnish | 2019-08-19 – 2019-09-09 |
| 3001 | KT2021-3A | 2024-01-08 – 2024-04-30 | Juho Pölönen | Finnish | 2023-12-01 – 2024-01-12 |
| 3002 | KT2021V-3, KT2021V-3A | 2024-01-08 – 2024-04-30 | Juho Pölönen | Finnish | 2023-12-01 – 2024-01-12 |
| 3004 | KT2022-3A, KT2022-3C | 2025-01-07 – 2025-04-30 | Juho Pölönen | Finnish | 2024-12-01 – 2025-01-13 |
| 3005 | KT2023-A, KT2023-C | 2026-01-07 – 2026-04-30 | Juho Pölönen | Finnish | 2025-12-01 – 2026-01-13 |
| 3006 | KT2023V-A | 2026-01-07 – 2026-05-24 | Juho Pölönen | Finnish | 2025-12-01 – 2026-01-13 |
The descriptions shown below are for the academic year: 2027-2028
Learning Outcomes
After completing the course, students will understand the structure and hierarchy of larger automation systems and be able to analyze their functional entities. They will master the principles of PC-based control systems for industrial automation and be able to program and use them in machine and industrial automation applications.
The student will be able to implement motion control solutions for different types of motors and to design and program user interfaces for industrial automation applications. They will understand the interfaces to cloud services at the control level and be able to use them for data processing and remote monitoring.
The student will be familiar with machine vision applications in industrial automation and robotics. The student will be able to implement and program machine vision systems for the most typical applications in robotics and quality control.
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
Mechanical Automation 2
Contents
- Structure, hierarchy and design of automation systems
- PC-based control systems and more efficient programmable logic controllers
- Advanced programming methods
- Motion control and servo motors
- Web-based interfaces and interfaces to cloud services
- Machine vision
Recommended or Required Reading and Other Learning Resources/Tools
- Teacher's lecture material
- Hardware manuals and data sheets
- Other material to be distributed
Mode of Delivery / Planned Learning Activities and Teaching Methods
-Lectures
-Laboratory exercises
-Project work
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
Lectures, exercises and project work.