Competing risk models in reliability systems, an Exponential distribution model with Gamma prior distribution, a Bayesian analysis approach

Ismed, Iskandar and Muchamad, Oktaviandri and R., Wangsaputra and Zamzuri, Hamedon (2019) Competing risk models in reliability systems, an Exponential distribution model with Gamma prior distribution, a Bayesian analysis approach. In: iMEC-APCOMS 2019: Proceedings of the 4th International Manufacturing Engineering Conference and The 5th Asia Pacific Conference on Manufacturing Systems , 21-22 August 2019 , Putrajaya, Malaysia. pp. 335-341.. ISBN 978-981-15-0950-6

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Abstract

This paper is a second paper on the use of Exponential distribution in competing risk problems. The difference is this model is developed using Gamma distribution as its prior distribution. For the cases where the failure data together with their causes of failure are simply quantitatively inadequate, time consuming and expensive to perform the life tests, especially in engineering areas, Bayesian analysis approach is used. This model is limited for independent causes of failure. In this paper our effort is to introduce the basic notions that constitute an exponential competing risks model in reliability using Bayesian analysis approach and presenting their analytic methods. Once the model has been develop through the system likelihood function and individual posterior distributions then the parameter of estimates are derived. The results are the estimations of the failure rate of individual risk, the MTTF of individual and system risks, and the reliability estimations of the individual and of the system of the model.

Item Type:	Conference or Workshop Item (Lecture)
Uncontrolled Keywords:	Reliability; Competing Risks; Exponential Distribution; Bayesian
Subjects:	T Technology > TP Chemical technology T Technology > TS Manufactures
Faculty/Division:	Faculty of Mechanical & Manufacturing Engineering
Depositing User:	Pn. Hazlinda Abd Rahman
Date Deposited:	06 Apr 2020 03:56
Last Modified:	06 Apr 2020 03:56
URI:	http://umpir.ump.edu.my/id/eprint/27617
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