Competing Risk Models in Reliability Systems, a Weibull Distribution Model with Bayesian Analysis Approach

In reliability theory, the most important problem is to determine the reliability of a complex system from the reliability of its components. The weakness of most reliability theories is that the systems are described and explained as simply functioning or failed. In many real situations, the failur...

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Main Authors:	Ismed, Iskandar, Yudi Satria, Gondokaryono
Format:	Conference or Workshop Item
Language:	English English
Published:	2015
Subjects:	TS Manufactures
Online Access:	http://umpir.ump.edu.my/id/eprint/11562/ http://umpir.ump.edu.my/id/eprint/11562/1/Competing%20risk%20models%20in%20reliability%20systems%2C%20a%20weibull.pdf http://umpir.ump.edu.my/id/eprint/11562/7/Competing%20risk%20models%20in%20reliability%20systems%2C%20a%20weibull-abstract.pdf

id	oai:umpir.ump.edu.my:11562
recordtype	eprints
spelling	oai:umpir.ump.edu.my:115622015-12-03T02:18:15Z http://umpir.ump.edu.my/id/eprint/11562/ Competing Risk Models in Reliability Systems, a Weibull Distribution Model with Bayesian Analysis Approach Ismed, Iskandar Yudi Satria, Gondokaryono TS Manufactures In reliability theory, the most important problem is to determine the reliability of a complex system from the reliability of its components. The weakness of most reliability theories is that the systems are described and explained as simply functioning or failed. In many real situations, the failures may be from many causes depending upon the age and the environment of the system and its components. Another problem in reliability theory is one of estimating the parameters of the assumed failure models. The estimation may be based on data collected over censored or uncensored life tests. In many reliability problems, the failure data are simply quantitatively inadequate, especially in engineering design and maintenance system. The Bayesian analyses are more beneficial than the classical one in such cases. The Bayesian estimation analyses allow us to combine past knowledge or experience in the form of an apriori distribution with life test data to make inferences of the parameter of interest . In this paper, we have investigated the application of the Bayesian estimation analyses to competing risk systems. The cases are limited to the models with independent causes of failure by using the Weibull distribution as our model. A simulation is conducted for this distribution with the objectives of verifying the models and the estimators and investigating the performance of the estimators for varying sample size. The simulation data are analyzed by using Bayesian and the maximum likelihood analyses. The simulation results show that the change of the true of parameter relatively to another will change the value of standard deviation in an opposite direction. For a perfect information on the prior distribution, the estimation methods of the Bayesian analyses are better than those of the maximum likelihood. The sensitivity analyses show some amount of sensitivity over the shifts of the prior locations. They also show the robustness of the Bayesian analysis within the range between the true value and the maximum likelihood estimated value lines. 2015 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/11562/1/Competing%20risk%20models%20in%20reliability%20systems%2C%20a%20weibull.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/11562/7/Competing%20risk%20models%20in%20reliability%20systems%2C%20a%20weibull-abstract.pdf Ismed, Iskandar and Yudi Satria, Gondokaryono (2015) Competing Risk Models in Reliability Systems, a Weibull Distribution Model with Bayesian Analysis Approach. In: Joint Conference Imec-Apcoms 2015 Universiti Malaysia Pahang (Ump) and Institut Teknologi Bandung (ITB), Indonesia, 12-14 November 2015 , Kuala Lumpur. pp. 1-8.. (Unpublished)
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English English
topic	TS Manufactures
spellingShingle	TS Manufactures Ismed, Iskandar Yudi Satria, Gondokaryono Competing Risk Models in Reliability Systems, a Weibull Distribution Model with Bayesian Analysis Approach
description	In reliability theory, the most important problem is to determine the reliability of a complex system from the reliability of its components. The weakness of most reliability theories is that the systems are described and explained as simply functioning or failed. In many real situations, the failures may be from many causes depending upon the age and the environment of the system and its components. Another problem in reliability theory is one of estimating the parameters of the assumed failure models. The estimation may be based on data collected over censored or uncensored life tests. In many reliability problems, the failure data are simply quantitatively inadequate, especially in engineering design and maintenance system. The Bayesian analyses are more beneficial than the classical one in such cases. The Bayesian estimation analyses allow us to combine past knowledge or experience in the form of an apriori distribution with life test data to make inferences of the parameter of interest . In this paper, we have investigated the application of the Bayesian estimation analyses to competing risk systems. The cases are limited to the models with independent causes of failure by using the Weibull distribution as our model. A simulation is conducted for this distribution with the objectives of verifying the models and the estimators and investigating the performance of the estimators for varying sample size. The simulation data are analyzed by using Bayesian and the maximum likelihood analyses. The simulation results show that the change of the true of parameter relatively to another will change the value of standard deviation in an opposite direction. For a perfect information on the prior distribution, the estimation methods of the Bayesian analyses are better than those of the maximum likelihood. The sensitivity analyses show some amount of sensitivity over the shifts of the prior locations. They also show the robustness of the Bayesian analysis within the range between the true value and the maximum likelihood estimated value lines.
format	Conference or Workshop Item
author	Ismed, Iskandar Yudi Satria, Gondokaryono
author_facet	Ismed, Iskandar Yudi Satria, Gondokaryono
author_sort	Ismed, Iskandar
title	Competing Risk Models in Reliability Systems, a Weibull Distribution Model with Bayesian Analysis Approach
title_short	Competing Risk Models in Reliability Systems, a Weibull Distribution Model with Bayesian Analysis Approach
title_full	Competing Risk Models in Reliability Systems, a Weibull Distribution Model with Bayesian Analysis Approach
title_fullStr	Competing Risk Models in Reliability Systems, a Weibull Distribution Model with Bayesian Analysis Approach
title_full_unstemmed	Competing Risk Models in Reliability Systems, a Weibull Distribution Model with Bayesian Analysis Approach
title_sort	competing risk models in reliability systems, a weibull distribution model with bayesian analysis approach
publishDate	2015
url	http://umpir.ump.edu.my/id/eprint/11562/ http://umpir.ump.edu.my/id/eprint/11562/1/Competing%20risk%20models%20in%20reliability%20systems%2C%20a%20weibull.pdf http://umpir.ump.edu.my/id/eprint/11562/7/Competing%20risk%20models%20in%20reliability%20systems%2C%20a%20weibull-abstract.pdf
first_indexed	2018-09-07T01:32:28Z
last_indexed	2018-09-07T01:32:28Z
_version_	1610910478231404544

Competing Risk Models in Reliability Systems, a Weibull Distribution Model with Bayesian Analysis Approach

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