Condition Monitoring and Predictive Maintenance (IAM540)
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.
The course provides the engineering analysis methods to analyse industrial equipment and structures, failure modes, and 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, and radiography.
Course description for study year 2023-2024. Please note that changes may occur.
Semester tution start
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The course compiles eight modules together as follows:
Module 1 is about condition-based maintenance and its standard ISO 17359.
Module 2 is about the most common industrial faults like imbalance, misalignment, bent shaft, bearing defects, gear faults, structural cracks in pipes and pressure vessels, and faults for on-demand equipment.
Module 3 is about monitoring techniques, i.e. vibration, acoustic emission, ultrasonic, oil-debris, thermal and process parameters.
Module 4 is about non-destructive testing (NDT) methods such as penetrant, flux leakage, eddy current, and radiography.
Module 5 is about a generic project execution model to design condition-monitored and predictive maintenance-ready equipment, and monitoring engineering methods: failure mode and symptom analysis, diagnostic coverage analysis, and predictive maintenance analysis.
Module 6 is about signal analysis, time and frequency domain detection and diagnostics analysis
Module 7 is about Model-based prognostics and Data-driven Prognostics.
Module 8 is about prescriptive maintenance and estimating remaining useful lifetime (RUL) for potential prescriptive scenarios.
Lectures, lab experiments, teamwork, oral presentation, project management, and communication with real-world stakeholders and the condition monitoring community, are all activities and skills embedded into the course modules to scaffold the learning performance. The learning is assessed and reinforced by several assignments, lab experiments, oral presentations and a course project.
By completing this course, the students shall gain the following knowledge, skills and competencies:
- Gain a comprehensive understanding of condition monitoring (CM), condition-based maintenance (CBM) and predictive maintenance (PdM).
- Gain a comprehensive understanding of common machine faults: causes, mechanisms, symptoms, and modes.
- 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, and 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.
- can analyze relevant academic, professional, and research ethical problems
- can work in teams and plan and manage projects.
- can apply his/her knowledge and skills in new areas in order to carry out assignments and projects
- can communicate about academic issues, analyses and conclusions in the field, both with specialists and the general public
Required prerequisite knowledge
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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.