A Multiple-Model Reliability Prediction Approach for Condition-Based Maintenance

2018 ◽  
Vol 67 (3) ◽  
pp. 1364-1376 ◽  
Author(s):  
Kim Verbert ◽  
Bart De Schutter ◽  
Robert Babuska
Keyword(s):  
Condition Based Maintenance ◽  
Reliability Prediction ◽  
Multiple Model ◽  
Model Reliability ◽  
Prediction Approach

A Stochastic Approach to Integrated Vehicle Reliability Prediction

2009 ◽  
Author(s):  
Justin Madsen ◽  
Dan Ghiocel ◽  
David Gorsich ◽  
David Lamb ◽  
Dan Negrut
Keyword(s):  
Integrated Approach ◽  
Stochastic Approach ◽  
Reliability Prediction ◽  
Operational Environment ◽  
Research Project ◽  
Element Analysis ◽  
Ground Vehicle ◽  
Us Army ◽  
University Of Wisconsin ◽  
Prediction Approach

This paper addresses some aspects of an on-going multiyear research project of GP Technologies in collaboration with University of Wisconsin-Madison for US Army TARDEC. The focus of this research project is to enhance the overall vehicle reliability prediction process. A combination of stochastic models for both the vehicle and operational environment are utilized to determine the range of the system dynamic response. These dynamic results are used as inputs into a finite element analysis of stresses on subsystem components. Finally, resulting stresses are used for damage modeling and life and reliability predictions. This paper describes few selected aspects of the new integrated ground vehicle reliability prediction approach. The integrated approach combines the computational stochastic mechanics predictions with available statistical experimental databases for assessing vehicle system reliability. Such an integrated reliability prediction approach represents an essential part of an intelligent virtual prototyping environment for ground vehicle design and testing.

A Review on Development and Trend of Intelligent Maintenance System

2011 ◽  
Vol 314-316 ◽  
pp. 2365-2369
Author(s):  
Yin Hui Ao
Keyword(s):  
Feature Extraction ◽  
Performance Prediction ◽  
Future Trend ◽  
Condition Based Maintenance ◽  
Reliability Prediction ◽  
Health Evaluation ◽  
Maintenance System ◽  
Intelligent Maintenance ◽  
Key Technologies ◽  
Intelligent Maintenance System

Condition Based Maintenance (CBM) is becoming to be employed by many manufacturing factories. Performance prediction and multi objectives optimization are much needed in current CBM. The research of Intelligent Maintenance System grows rapidly. This paper summarized the key technologies of intelligent maintenance. It reviewed the recent research and developments in data acquisition, feature extraction, health evaluation and reliability prediction. The paper concludes with a brief discussion of possible future trend of intelligent maintenance.

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