Fault Detection Using Bayesian Networks provides an in-depth exploration of how Bayesian networks can be leveraged for fault detection in complex systems. Ideal for advanced undergraduate and graduate students in engineering, this course covers both the theoretical foundations and practical applications of Bayesian networks in process monitoring and fault diagnosis. Participants will gain:

• Comprehensive understanding of multivariate control charts and their implementation.
• Insight into Bayesian classifiers and their role in fault detection.
• Skills to develop and apply Bayesian network models for real-world industrial scenarios.
• Practical knowledge through case studies and hands-on projects.
• The ability to compare and contrast different fault detection methodologies.

By the end of this course, students will be equipped to design and implement effective fault detection systems using Bayesian networks, enhancing their ability to manage and troubleshoot complex industrial processes.