Content, progress and pedagogy of the module

Learning objectives

Knowledge

• Have comprehension of the benefits of preventive and predictive maintenance and condition monitoring in the industrial sector
• Have comprehension on the modern data driven approaches in condition monitoring
• Have comprehension of the concept of product data and Project Lifecycle Management (PLM) fundamentals
• Have comprehension of the use of databases and common data formats to manage, store and process data

Skills

• Be able to analyse data for vibrational machinery condition monitoring and fundamental of effects of vibration. Measuring equipment includes sensors, signal conditioners, and recording elements
• Be able to analyse typical case studies, and identifications of malfunctions
• Be able to implement data driven modelling for condition monitoring and anomaly detection
• Be able to assess the performance of data driven models for condition monitoring

Competences

• Be able to monitor the condition and develop measurable preventive maintenance for given service industry problems
• Be able to monitor machinery condition with vibration effects using various electronic equipment and scaled engineering approach
• Be able to compare modern data driven models and algorithms for condition monitoring
• Be able to apply a data driven approach to analyse and  implement condition monitoring methods

Type of instruction

The course module will be targeted with a mixture of lectures, self-preparatory presentation by students, and discussion on various real time case studies supplemented with e-learning activities.

Extent and expected workload

Since it is a 5 ECTS course module, the work load is expected to be 150 hours for the student.

Exam

Exams