Condition monitoring and predictive maintenance

ABSTRACT

The course aims to provide the conceptual, methodological, and practical mainstream methodologies and research for the Condition Monitoring and Predictive Maintenance of industrial equipment. At the end of the course, the student is able to apply the most advanced techniques based on Machine Learning, Neural Networks and Model-Based techniques, characterising Industry 4.0, of Condition Monitoring and Predictive Maintenance. Finally, significant cases related to industrial machines will be analyzed by Matlab/Simulink case studies.

SCHEDULE

• 8th October, 9 am-5pm - Room III - via Risorgimento, 4 (Bologna)
• 9th October, 9 am-5pm - Room III - via Risorgimento, 4 (Bologna)
• 15th October, 2pm-6pm - Room 7.7 - via Saragozza, 8 (Bologna)

Exam: 25th October, 9am-11am - Room 5.1 - via Risorgimento, 2 (Bologna)

This course is part of the training provided for IBES PhD Students in the academic year 2023/2024.

Those who succesfully attend and complete the course:

• are eligible for max. 3 credits if they are enrolled in cycle 37;
• gain 20 attendance hours of the IBES training for the Automatic Control and Operational Research (ARO) curriculum if they are enrolled in cycle 38 and 39.

Check the links above for further information about the specific academic requirements for each cyle and how to comply with them.