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Production automation (5 cr)

Code: 8I00CG72-3005

General information


Enrollment
22.04.2025 - 03.09.2025
Registration for the implementation has begun.
Timing
29.08.2025 - 31.12.2025
The implementation has not yet started.
Number of ECTS credits allocated
5 cr
Local portion
5 cr
Mode of delivery
Contact learning
Unit
SeAMK Master School
Campus
SeAMK Seinäjoki, Frami
Teaching languages
Finnish
Degree programmes
Master's Degree Programme in Automation Engineering
Teachers
Jarkko Pakkanen
Juha Hirvonen
Scheduling groups
Avoin AMK (Ei koske tutkinto-opiskelijaa) (Size: 10 . Open UAS : 10.)
Groups
YAUTE25
Master of Engineering, Automation Engineering
Small groups
Open UAS (Doesn't apply to degree student)
Course
8I00CG72

Evaluation scale

1-5

Objective

Student knows the principles of machine vision systems and can apply machine vision technology in industrial automation. Student can develop a production cell, which utilizes industrial robots and machine vision system. Student can utilize mobile and collaboration robotics in industrial automation.

Content

- Machine vision systems in manufacturing industry
- Robotics and its applications
- Robot simulation and offline programming
- Robot programming
- Collaborative robotics
- Mobile robotics

Materials

Will be distributed during the course.

Teaching methods

Five independent exercise works that are related to robotics, machine vision and collaboration between them.
Contact lessons that support the exercise works.

Student workload

Contact sessions: 28h
Independent studying

Assessment criteria, satisfactory (1)

Student knows the basics of machine vision systems. Student knows how the industrial robots are used in industrial automation.

Assessment criteria, good (3)

Student knows the principles of machine systems and can apply machine vision technology in industrial automation. Student can develop a production cell, which utilizes industrial robots and machine vision system. Student can utilize mobile and collaboration robotics in industrial automation.

Assessment criteria, excellent (5)

Student have a good understanding of machine vision technology. Student can develop a production cell, which utilizes industrial robots and machine vision system. Student can utilize mobile and collaborative robotics in industrial automation.

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