Course content

The course provides competence and research experience in the engineering profession at the master level. Students do a specialisation project within mechatronics and automation typically in collaboration with an academic research group and under supervision. The supervisor, student, and research group contributes to formulate and adapt the project description. Study material and resources will be adapted to the project and updated as the project progresses.

Learning outcome

Competence:

Upon completing the course, the candidate can, within the context of mechatronics and automation in research and innovation:

• identify problems, challenges, and systems which can be solved, designed, controlled, or improved.
• work and contribute as a part of an academic research group.
• work individually on interdisciplinary projects.
• demonstrate aspects of team and project management skills.
• present problems, solutions and results both orally and written in a professional and scientific manner and adapted to the audience as needed.
• Demonstrate the ability and willingness for lifelong learning in automation and mechatronics through a genuine interest in scientific exploration and independent development work.

Knowledge and skills:

Upon completing the course, the candidate can, within the scope and context of the project

• explain, assess, compare, and use theory, methods and tools for design, implementation, and testing of solutions and systems within mechatronics and automation.
• identify and discuss complex challenges faced by various stakeholders in the private and public sector and acknowledge future potential and pitfall in a changing world.
• gather and critically assess technical and scientific information.
• explain and discuss aspects of sustainability, societal impact, and ethical issues in both the selected solution and alternative ones.
• identify potential for innovation, propose solutions, and discuss business aspects

Learning methods and activities

The course can be considered as guided self-study and work experience by completing a project in a research-based setting. Learning activities are thus comprised of a variety of tasks needed to complete the project, including project planning, management, execution, and reporting.

Compulsory assignments

• Compulsory learning activities

Further on evaluation

The final grade is based on an overall evaluation of the portfolio, which consists of work that is carried out, documented and digitally submitted during the term. Assignments are designed to help students achieve specific course learning outcomes, and formative feedback is given during the period of the portfolio. The re-sit exam is a portfolio submission in August the following year. Students who failed the ordinary exam can re-submit an improved version of their portfolio.

Specific conditions

Recommended previous knowledge

It is highly recommended to have completed all preceding courses in the master programme.

Required previous knowledge

Students must have completed at least 45 credits of the 60 credits in total from the first year of the master programme. In addition, it is a requirement that students have passed AIS4104 Robotics and Intelligent Systems with Project. Finally, it is a requirement that students are enrolled in the study programme to which the course belongs.

Course materials

An updated course overview, including curriculum, is presented at the start of the semester. Suggestions for self-study material relevant for the project may be given through the semester.

Credit reductions