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Title: Updating time-to-failure distributions based on field observations and sensor data.

Abstract

Enterprise level logistics and prognostics and health management (PHM) modeling efforts use reliability focused failure distributions to characterize the probability of failure over the lifetime of a component. This research characterized the Sandia National Laboratories developed combined lifecycle (CMBL) distribution and explored methods for updating this distribution as systems age and new failure data becomes available. The initial results obtained in applying a Bayesian sequential updating methodology to the CMBL distribution shows promise. This research also resulted in the development of a closed-form full life cycle (CFLC) distribution similar to the CMBL distribution but with slightly different, yet commonly recognized, input parameters. Further research is warranted to provide additional theoretical validation of the distributions, complete the updating methods for the CMBL distribution, evaluate a Bayesian updating methodology for the CFLC distribution, and determine which updating methods would be most appropriate for enterprise level logistics and PHM modeling.

Authors:
; ;
Publication Date:
Research Org.:
Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
896865
Report Number(s):
SAND2006-6890
TRN: US200704%%29
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; FAILURES; DISTRIBUTION; SERVICE LIFE; MANAGEMENT; PROBABILITY; RELIABILITY; COMPUTERIZED SIMULATION; Failure analysis.; Product life cycle-Mathematical models.; Failure time data analysis.; Sensors.

Citation Formats

Lowder, Kelly S, Briand, Daniel, and Shirah, Donald. Updating time-to-failure distributions based on field observations and sensor data.. United States: N. p., 2006. Web. doi:10.2172/896865.
Lowder, Kelly S, Briand, Daniel, & Shirah, Donald. Updating time-to-failure distributions based on field observations and sensor data.. United States. https://doi.org/10.2172/896865
Lowder, Kelly S, Briand, Daniel, and Shirah, Donald. 2006. "Updating time-to-failure distributions based on field observations and sensor data.". United States. https://doi.org/10.2172/896865. https://www.osti.gov/servlets/purl/896865.
@article{osti_896865,
title = {Updating time-to-failure distributions based on field observations and sensor data.},
author = {Lowder, Kelly S and Briand, Daniel and Shirah, Donald},
abstractNote = {Enterprise level logistics and prognostics and health management (PHM) modeling efforts use reliability focused failure distributions to characterize the probability of failure over the lifetime of a component. This research characterized the Sandia National Laboratories developed combined lifecycle (CMBL) distribution and explored methods for updating this distribution as systems age and new failure data becomes available. The initial results obtained in applying a Bayesian sequential updating methodology to the CMBL distribution shows promise. This research also resulted in the development of a closed-form full life cycle (CFLC) distribution similar to the CMBL distribution but with slightly different, yet commonly recognized, input parameters. Further research is warranted to provide additional theoretical validation of the distributions, complete the updating methods for the CMBL distribution, evaluate a Bayesian updating methodology for the CFLC distribution, and determine which updating methods would be most appropriate for enterprise level logistics and PHM modeling.},
doi = {10.2172/896865},
url = {https://www.osti.gov/biblio/896865}, journal = {},
number = ,
volume = ,
place = {United States},
year = {2006},
month = {10}
}