Michael Pecht1 , C.H. Wu2, C.H. Yang2, S.C. Lo3, N. Vichare4, E. Rhem4
1CALCE, Center for Advanced Life Cycle Engineering, Department of Mechanical Engineering, University of Maryland, College Park, Maryland 20740, USA
2Graduate Institute of Mechanical and Electrical Engineering, National Taipei University of Technology, Taipei, Taiwan
3Graduate Institute of Information and Logistics Management, National Taipei University of Technology, Taipei, Taiwan
4Dell Client Systems Reliability Engineering, Dell Computer Corp., Austin, TX, USA
This study focuses on the development of automation platform for performing data mining on a telemetry
database for computer systems. It is common for computer systems to encounter failures in an unexpected
manner. It is therefore valuable to have prognostics capability for computer systems to minimize
the effects of unexpected system failure. Data acquisition schemes employing telemetry techniques are
considered the most effective method for collection of in-service information for computer systems.
Analysis of an enormous telemetry database of high complexity must be completed before useful knowledge
can be extracted. In this research, an automatic data mining platform is reported for the extraction
of useful knowledge from the telemetry database. This paper describes the structure and basic theories
underlying the data mining of the telemetry database. Also, an automatic computer program capable
of performing database management, filtering, data analysis, and reporting is described. Some useful data
generated by the platform are reported for the telemetry database.