Condition Monitoring and Predictive Maintenance (OFF540)

The course deals with condition monitoring and predictive maintenance of dynamic machinery and static mechanical equipment. The course provides the project execution model to design and manage condition-based maintenance and predictive maintenance programs.


Course description for study year 2022-2023

Facts

Course code

OFF540

Version

1

Credits (ECTS)

5

Semester tution start

Spring

Number of semesters

1

Exam semester

Spring

Language of instruction

English

Offered by
Time table

View course schedule

Content

The course provides the engineering analysis methods to analyse industrial equipment and structures, failure modes, failure symptoms and determine suitable monitoring techniques (vibration, acoustic emission, ultrasonic, oil-debris, thermal and process parameters) and the required technical specifications.

The course provides basic hands-on practics to perform signal analysis, detection analysis, diagnosis and prognosis analysis.

The course focuses on detecting the most common industrial faults like imbalance, misalignment, bent shaft, bearing defects, gear faults, structural cracks in pipes piping and pressure vessels, and faults for on-demand equipment.

The non-destructive testing (NDT) methods are also provided such as penetrant, flux leakage, eddy current, radiography.

Learning outcome

By completing this course, the students shall
  • Gain a comprehensive understanding of condition monitoring (CM), condition-based maintenance (CBM) and predictive maintenance (PdM).
  • Gain a basic understanding and theories behind the monitoring techniques, e.g. vibration, acoustic emission, ultrasonic, oil-debris, thermal and process parameters.
  • Gain a basic understanding and theories behind signal analysis (time and frequency domains), diagnosis and prognosis analysis.
  • Gain a basic understanding and theories behind the non-destructive testing (NDT) methods such as penetrant, flux leakage, eddy current, radiography.
  • Be able to apply the project execution model to design monitored and PdM-ready equipment and deliver Concept and front-end engineering (FEED) studies.
  • Be able to perform engineering analysis methods, e.g. Failure modes analysis, Symptoms Analysis, Sensor diagnostic coverage analysis, PdM concept study.
  • Be able to perform time and frequency domain signal analysis.
  • Be able to perform diagnosis analysis and determine the fault type, location and severity level.
  • Be able to perform prognosis analysis (physics-based and/or data-driven) to predict the remaining useful lifetime.

Required prerequisite knowledge

None

Exam

Project work and oral presentation

Form of assessment Weight Duration Marks Aid
Project work in groups 9/10 Letter grades
Oral presentation 1/10 Letter grades

All assessment parts must be passed to achieve an overall grade in the course. There are no re-sit opportunities on the project assignment, if students want to take this part again, they must take the course again the next time the course is lectured.Students who do not attend the presentation cannot expect to take this part again. If there is a valid absence, the student can, by agreement with the subject teacher, complete the presentation at a later date.Students who do not pass one of the assessment sections, or wish to improve their grades, must retake all assessment sections within the same semester in order to obtain a new overall grade.

Coursework requirements

Guest lectures, 3 lab exercises, company visit
Laboratory exercises, company visits, guest lectures.

Course teacher(s)

Course coordinator:

Idriss El-Thalji

Head of Department:

Mona Wetrhus Minde

Method of work

Lectures, assignment, laboratory exercises, company visits, guest lectures.

Overlapping courses

Course Reduction (SP)
Condition monitoring and management (MOM350_1) 5

Open for

Master's level at the Faculty of Science and Technology.

Course assessment

Standard forms and/or discussion.

Literature

The syllabus can be found in Leganto