Course content

The curriculum is adapted to the candidate's project and within the fields of mechatronics and automation, including topics such as:

• Design, prototyping, and integration of mechatronic systems
• Industry 4.0 and digital manufacturing
• Digital twins, condition monitoring, predictive maintenance, and automated cyber-physical systems
• Mathematical modelling and simulation of dynamical systems
• Computer engineering, programming, artificial intelligence, machine learning, and machine vision
• Robotics, control systems, and intelligent machines
• Mechanical engineering, mechanics, and electronics
• Possibly other topics

Learning outcome

Competence (knowledge, skills, and general competence)

Upon completion of the master thesis, the candidate can

• explain, from a scholarly perspective, the theories and methods currently used to develop advanced solutions in automation and mechatronics; demonstrate expertise through project-based design, implementation, and application; and analyse and discuss the strengths and weaknesses of such solutions.
• identify and analyse complex challenges within the industrial and maritime sectors, taking into account the possibilities in a constantly changing world.
• explain, assess, compare, and apply advanced methods and tools for the design, implementation, and testing of solutions and systems in automation and mechatronics.
• gather and critically evaluate technical and scientific information within automation and mechatronics and related fields.
• apply theories, methods, and principles for the design and implementation of sustainable solutions in automation and mechatronics.
• utilize advanced research and development knowledge to contribute to the development and implementation of automated mechatronic systems.
• identify innovation potential, develop proposals for solutions, and demonstrate business understanding of challenges in automation and mechatronics.
• identify and analyze societal challenges and potential solutions rooted in automation and mechatronics, as well as the consequences and future scenarios of these.
• reflect on ethical and sustainability norms at individual, societal, and global levels, and apply them in own work.
• work individually and purposefully, take initiative, collaborate effectively in teams, and demonstrate leadership in project and development work in an organization.
• communicate appropriately, engage in dialogue, and discuss professionally with various stakeholders of a technological solution.
• show the ability and willingness for lifelong learning in automation and mechatronics through a genuine interest in scholarly exploration and independent development work.

Learning methods and activities

The master thesis is independent project work. The student will have at least one supervisor from NTNU and one from an associate partner in the project, usually a company or research group. The student is responsible for arranging regular meetings with supervisors.

All formal requirements must be satisfied and all mandatory work must be approved within set deadlines, including a pre-project report at the start of the semester, for undertaking the project. Otherwise, supervisors and external partners have no obligations with respect to the project.

More details about formal requirements and mandatory work will be provided to students before the start of the master thesis.

Please see the following webpage for more information: https://i.ntnu.no/masteroppgave

Further on evaluation

All formal requirements must be satisfied for the master thesis to be assessed. Please see the following webpage for more information: https://i.ntnu.no/masteroppgave

In addition, all mandatory work must be completed for the thesis to be assessed, including approval of a pre-project report at the start of the semester.

Notes:

• The thesis must reflect upon the project's relevance with respect to sustainability and the UN's sustainable development goals.
• A declaration concerning use of generative AI tools in the thesis must accompany the submission.

Specific conditions

Required previous knowledge

Students must have completed all preceding courses or equivalent corresponding to 90 ECTS.

Course materials

Please see the following webpage for more information: https://i.ntnu.no/masteroppgave