Robotic Based Condition Monitoring

2024/2025

Content, progress and pedagogy of the module

Learning objectives

Knowledge

  • Have knowledge and comprehension for how to use robotic systems for condition monitoring
  • Have knowledge and comprehension within maintenance schemes, economic benefits, scope and limitations
  • Have knowledge and comprehension within maintenance strategies applied to various problems in the industrial sector

Skills

  • Be able to use and integrate multiple sensors in robotic systems for condition monitoring
  • Be able to judge the usefulness of the different scientific methods for the design of diagnostic, and condition monitoring systems
  • Be able to verify the different scientific analysis and methods by laboratory experiments
  • Be able to use and adapt algorithms and models from artificial intelligence and machine learning to design condition monitoring systems using robots

Competences

  • Be able to control the working and development process within the project theme, and be able to develop new solutions within diagnostic, condition monitoring, and maintenance of energy systems
  • Be able to set up innovative ideas within the area of condition monitoring, diagnostic and maintenance
  • Independently be able to continue own development in competence and specialisation related to the field

Type of instruction

Problem based project organised project work in groups.

The project can be a disciplinary project, a cross disciplinary project or a part of a multi-disciplinary project, where several groups from the department do different parts of a larger project. Finally, the project can also be a part of a so-called MEGA project, where several project groups from more departments are participating, each doing their part of the large project to find a total solution.

Project work including supervision may be supplemented with lectures, workshops, presentation seminars, consultant meetings regarding PBL content, laboratory tests, etc.

The considered system should be analysed, and models and simulations of the system are to be made. Different methods are to be applied to find the parameters of the system.

The set-up models should be verified by experimental test either directly on a real system or on a model or parts of the scaled systems set-up in the laboratory. 

The project work must be documented in a scientific way by a summary report, a paper and a poster as described under "Additional Information".

The summary report should include both the problem analysis, problem formulation, methodology and implementation as it would be in the case of a standard project report.

Extent and expected workload

Since it is a 15 ECTS project module, the workload is expected to be 450 hours for the student.

Exam

Prerequisite for enrollment for the exam

  • It is a precondition that students participate in the Conference for MSc Esbjerg Students (CES). Students are required to prepare a scientific paper and a poster which must be presented at the conference
  • In case of a re-exam, the student will have to present the scientific paper and poster in front of a committee made up of the supervisor and at least one internal adjudicator.

Exams

Name of examRobotic Based Condition Monitoring
Type of exam
Oral exam based on a project
The project group should orally present the project work and scientific paper as specified in the Examination Policies and Procedures. The project group members will undergo an oral examination with internal adjudicator, based on the scientific paper, poster and the project summary report.
ECTS15
Permitted aids
With certain aids:
For more information about permitted aids, please visit the course description in Moodle.
Assessment7-point grading scale
Type of gradingInternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Additional information

Examination format

The exam will be based on the documentation submitted and the rules in "Guidance for the Project of 1st Semester MSc in AI and Autonomous Systems", see below.

Guidance for the Project of 1st Semester MSc in AI and Autonomous Systems

1. Demands to the project documentation

The project should fulfil the objectives of the 1st semester project theme and should be documented to an acceptable technical and scientific level. The documentation shall include a scientific paper and a poster, which shall fulfil the standard for an international conference, e.g. the IEEE specifications. Moreover, the documentation shall include a project summary report - see below.

2.  Project documentation

The following material must be uploaded to the system “Digital Exam” on the date given for the submission:

  • Scientific paper, max. 10 pages, which presents the primary content and results of the project work
  • Project summary report (see below)
  • Project poster

3.  Conference participation

The paper must be presented, by one or more group members at a conference arranged within the Department of Energy. The conference will be run in the same manner as an international conference. The project poster must also be presented at this conference. All group members must attend the conference and the poster session to be allowed to participate in the project examination.

4.  Project summary report

The project summary report should elaborate the project details and conclusions. The maximum length of the summaryreport (report without appendices) is 50 pages. For more information see semester description in Moodle.

5.  Project exam

The project evaluation will take place at a later date than the conference.

At the project examination the project group shall present its project work in accordance to the Examination Policies and Procedures.

The presentation and assessment of the project is conducted in English.

Facts about the module

Danish titleRobotbaseret tilstandsovervågning
Module codeE-AIAS-K1-1
Module typeProject
Duration1 semester
SemesterAutumn
ECTS15
Language of instructionEnglish
Location of the lectureCampus Esbjerg
Responsible for the module

Organisation

Education ownerMaster of Science (MSc) in Engineering (Advanced Power Electronics)
Study BoardStudy Board of Build, Energy, Electronics and Mechanics in Esbjerg
DepartmentDepartment of Energy
FacultyThe Faculty of Engineering and Science