Prognostics and Health Management

Course Overview
Course Outline
Past Customers
Related Texts

Instructors
Contact


Course Overview

The course presents the tools and techniques for development and implementation of prognostics and health monitoring in terms of novel methods for in-situ monitoring, approaches for resource efficient data collection, algorithms for data reduction and parameter extraction, methods for identifying and analyzing precursors based on failure mechanisms, and techniques for predictions that can be used for assisting maintenance and logistics decisions. Different approaches for prognostics are presented along with implementation case-studies.

 

Course Outline

1. Prognostics and health management

2. Needs and benefits of prognostics

3. Approaches for prognostics

      • Fuses and canaries
      • Monitoring failure precursors
      • Monitoring environmental and usage exposures

4. Life cycle profile development

5. Failure modes, mechanisms, and effects analysis for selection of monitoring parameter

6. Data driven prognostic approaches

      • Data and pattern exploration
      • Multivariate state estimation technique
      • Principal component analysis
      • Mahalanobis distance

7. Examples and case studies of prognostics and health management

      • Impedance analysis as a prognostics technique for detection of interconnect degradation
      • Failure prognostics of multilayer ceramic capacitor in temperature-humidity-bias conditions
      • Identification and investigation of critical failure mechanisms and failure precursors for insulated gate bipolar transistor

8. Cost benefit analysis for PHM

 

Past Customers

  • Hong Kong University of Science and Technology (IEEE CPMT Hong Kong Chapter)

 

Related Texts

 

Contact


Michael Pecht
301-405-5323
education@calce.umd.edu
Bldg. 89, Room 1103
University of Maryland
College Park, MD 20742


 

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