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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

  • TAR22S1
    Bachelor'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

Objectives

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

Learning materials and recommended literature

Materials in the e-learning environment.

Teaching methods

- independent study
- distance learning and remote lectures
- webinars
- small group learning
- learning tasks

Exam dates and retake possibilities

The possible date and method of the exam will be announced in the course opening.

Alternative completion methods

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 for students

The evaluation is based on the qualitative evaluation of the exam and exercises/assignments.

Evaluation scale

0-5

Evaluation criteria, satisfactory (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.

Evaluation criteria, good (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.

Evaluation criteria, excellent (5)

Excellent (5): Student masters key subjects and is able to apply them creatively and innovatively.

Prerequisites

Fundamentals in technology, programming skills