The purpose of this three-day tutorial is to introduce attendees to empirical modeling techniques for process and equipment monitoring and prognostics.  On the first two days the tutorial will provide a background and an overview of equipment condition monitoring, detection, and identification because those are integral to a prognostics system.  On the second day, several prognostic techniques will be introduced with a brief background and basic theoretical foundations. The course will be applications oriented in that the assumptions inherent in the techniques will be explained so that the appropriate technique can be selected and applied to solve specific engineering problems.  Several understandable case studies will be presented so that attendees can see the general application of these technologies.

RESOURCE MATERIAL PROVIDED
Lecture notes.

COURSE SCHEDULE
Monday, August 12, 2013
The empirical modeling portion of the tutorial will discuss model development including:

• Parametric and non-parametric empirical modeling methods.
• Data cleaning and training set selection.
• Performance measures.

• The nature and sources of uncertainty.
• Fault detection techniques.
• Case Studies

• Conventional reliability-based using failure times (e.g. Weibull analysis)
• Population based with environmental considerations (e.g. proportional hazards modeling)
• Individual based (e.g. general path model)

INSTRUCTORS
Dr. J. Wesley Hines is a Professor and Department Head in the Department of Nuclear Engineering and the Director of the Reliability and Maintainability Education Program at the University of Tennessee.  Dr. Hines has applied advanced statistical methodologies to solving engineering problems for the past twenty years and teaches courses in reliability, condition monitoring, and prognostics.

*If taking both Course 1 and 2 consecutively, the price will be $1,495