Abstract Details
Activity Number:
|
206
|
Type:
|
Invited
|
Date/Time:
|
Monday, August 4, 2014 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Quality and Productivity Section
|
Abstract #310605
|
View Presentation
|
Title:
|
Field Failure Prediction Based on Multi-Level Repair and System Usage Information
|
Author(s):
|
William Q. Meeker*+ and Yili Hong and Zhibing Xu
|
Companies:
|
Iowa State University and Virginia Tech and Virginia Tech
|
Keywords:
|
Maintenance ;
Recurrence data ;
System Reliability ;
Trend Renewal Process
|
Abstract:
|
Repairable systems in the field often receive repair actions at different levels. For example, a truck may have an engine replaced or have a component of the engine replaced. Thus we may consider three levels: system (truck), sub-system (engine), and component level. At the system level, system usage and environmental information may also be available. At the sub-system and component levels, repair information may also be available through maintenance records. When the focus is on event process modeling and prediction of the component remaining life or replacements, multiple factors from different levels can affect the component failure process. In this paper, we develop a multi-level trend renewal process model to describe the event process for the component replacements. The proposed model can incorporate information from different levels and can explain the effects of factors at different levels on component failures. A field failure prediction procedure is also developed for the proposed model.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2014 program
|
2014 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Professional Development program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.