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Production automation (5 cr)

Code: 8I00CG72-3004

General information


Enrollment

17.04.2023 - 06.09.2023

Timing

28.08.2023 - 17.12.2023

Credits

5 op

Teaching languages

  • Finnish

Degree programmes

  • Master's Degree Programme in Automation Engineering

Teachers

  • Jarkko Pakkanen
  • Juha Hirvonen

Student groups

  • YAUTE23
    Master of Engineering, Automation Engineering

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

Evaluation scale

1-5

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.

Assessment methods and criteria

The accepted laboratory works are the basis of assessment. The assessment criteria are
- the extent of the work
- the rationality of the solution
- the neatness of the implementation
- reporting

Assessment criteria, satisfactory (1)

The student has not completed the laboratory works.

Assessment criteria, good (3)

The completed works are narrow and their implementation and reporting is a bit unclear.

Assessment criteria, excellent (5)

The completed works fulfill the requirements, their implementation is reasonable and the reporting is clear.

Assessment criteria, approved/failed

The completed works are highly extensive, their implementation is smooth and smart and the reporting is really clear and illustrative.