Short Course

Overview of Analytics for PHM

This course is intended for engineers, scientists, and managers who are interested in data driven methods for asset health management. You will learn how to asses potential projects, identify appropriate data sets, evaluate and select models, assess the performance of pilot projects (either internal or from third-party vendors), and deploy asset monitoring systems.

By the end of the course, you will have an understanding of what makes for a successful PHM project, how to assess vendors’ often unrealistic claims, and how to deploy a data-driven PHM system with the greatest chance of success.

■ Topics include
No Topics
1 Overview of data-driven PHM
2 Machine learning - introduction and concepts
3 Classification
4 Regression
5 Identifying a Good Project
6 Introduction to Neural Networks
7 Characterizing performance
8 Anomaly detection
9 Deep Learning
10 Applications
11 Practical Matters

Lecturer: Dr. Neil Eklund

… Bottom Line: Education is important to The PHM Society

Taking a course first is an excellent preparation to benefit from the conference and to meet students, professors and industry people from around the world and across diverse sectors.

Come for the entire conference and get reduced tuition. Special rates for fulltime students.

The educational and training experience is even better at the conference- free tutorials, workshops, peer-reviewed technical papers, poster sessions, technology demonstrations, doctoral symposium, data challenge and panel sessions. And the social events are planned to help make networking easy and enjoyable.

For information contact local coordinators: Jeff Bird:, Chao Jin: