Notice of Retraction Age replacement optimization with uncertainty of life time distribution parameters

2013 ◽  
Author(s):  
Liang Wen ◽  
Su Wu ◽  
Xi-Sheng Jia
Keyword(s):  
Time Distribution ◽  
Life Time ◽  
Distribution Parameters ◽  
Age Replacement

scholarly journals Harris Extended Power Lomax Distribution: Properties, Inference and Applications

2021 ◽  
Vol 10 (4) ◽  
pp. 77
Author(s):  
Adebisi Ade Ogunde ◽  
Victoria Eshomomoh Laoye ◽  
Ogbonnaya Nzie Ezichi ◽  
Kayode Oguntuase Balogun
Keyword(s):  
Time Distribution ◽  
Lorenz Curve ◽  
Life Time ◽  
Lomax Distribution ◽  
Proposed Model ◽  
Method Of Maximum Likelihood ◽  
Distribution Parameters ◽  
Rate Functions ◽  
New Distribution ◽  
Extended Power

In this work, we present a five-parameter life time distribution called Harris power Lomax (HPL)  distribution which is obtained by convoluting the Harris-G distribution and the Power Lomax distribution. When compared to the existing distributions, the new distribution exhibits a very flexible probability functions; which may be increasing, decreasing, J, and reversed J shapes been observed for the probability density and hazard rate functions. The structural properties of the new distribution are studied in detail which includes: moments, incomplete moment, Renyl entropy, order statistics, Bonferroni curve, and Lorenz curve etc. The HPL  distribution parameters are estimated by using the method of maximum likelihood. Monte Carlo simulation was carried out to investigate the performance of MLEs. Aircraft wind shield data and Glass fibre data applications demonstrate the applicability of the proposed model.

Lifetime Distribution Estimation of Boot Seals in Automotive Applications by Bayesian Method

2006 ◽  
Vol 129 (3) ◽  
pp. 275-282 ◽  
Author(s):  
Fabrice Guerin ◽  
Ridha Hambli
Keyword(s):  
Finite Element ◽  
Bayesian Method ◽  
Life Time ◽  
Automotive Applications ◽  
Fatigue Lifetime ◽  
Time Prediction ◽  
Steering Mechanism ◽  
Market Requirements ◽  
Distribution Parameters ◽  
Lifetime Testing

The constantly increasing market requirements of high quality vehicles ask for the automotive manufacturers to perform lifetime testing to verify the reliability levels of new products. A common problem is that only a small number of examples of a component of system can be tested. In the automotive applications, mechanical components subjected to cyclic loading have to be designed against fatigue. Boot seals are used to protect velocity joint and steering mechanisms in automobiles. These flexible components must accommodate the motions associated with angulation of the steering mechanism. Some regions of the boot seal are always in contact with an internal metal shaft, while other areas come into contact with the metal shaft during angulation. In addition, the boot seal may also come into contact with itself, both internally and externally. The contacting regions affect the performance and longevity of the boot seal. In this paper, the Bayesian estimation of lognormal distribution parameters (usually used to define the fatigue lifetime of rubber components) is studied to improve the accuracy of estimation in incorporating the available knowledge on the product. In particular, the finite element results and expert belief are considered as prior knowledge. For life time prediction by finite element method, a model based on Brown–Miller law was developed for the boot seal rubber-like material.

A general formula for the downtime distribution of a parallel system

1996 ◽  
Vol 33 (03) ◽  
pp. 772-785
Author(s):  
Harald Haukås ◽  
Terje Aven
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Time Distribution ◽  
Life Time ◽  
Exact Formula ◽  
Parallel System ◽  
System Failure ◽  
System Failures ◽  
Failure Scenario ◽  
Common Situation

In this paper we study the problem of computing the downtime distribution of a parallel system comprising stochastically identical components. It is assumed that the components are independent, with an exponential life-time distribution and an arbitrary repair time distribution. An exact formula is established for the distribution of the system downtime given a specific type of system failure scenario. It is shown by performing a Monte Carlo simulation that the portion of the system failures that occur as described by this scenario is close to one when we consider a system with quite available components, the most common situation in practice. Thus we can use the established formula as an approximation of the downtime distribution given system failure. The formula is compared with standard Markov expressions. Some possible extensions of the formula are presented.

Estimating life-time distribution by observing population continuously

2014 ◽  
Vol 79 ◽  
pp. 182-197 ◽  
Author(s):  
Hanhua Feng ◽  
Parijat Dube ◽  
Li Zhang
Keyword(s):  
Time Distribution ◽  
Life Time

A general formula for the downtime distribution of a parallel system

1996 ◽  
Vol 33 (3) ◽  
pp. 772-785 ◽  
Author(s):  
Harald Haukås ◽  
Terje Aven
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Time Distribution ◽  
Life Time ◽  
Exact Formula ◽  
Parallel System ◽  
System Failure ◽  
System Failures ◽  
Failure Scenario ◽  
Common Situation

In this paper we study the problem of computing the downtime distribution of a parallel system comprising stochastically identical components. It is assumed that the components are independent, with an exponential life-time distribution and an arbitrary repair time distribution. An exact formula is established for the distribution of the system downtime given a specific type of system failure scenario. It is shown by performing a Monte Carlo simulation that the portion of the system failures that occur as described by this scenario is close to one when we consider a system with quite available components, the most common situation in practice. Thus we can use the established formula as an approximation of the downtime distribution given system failure. The formula is compared with standard Markov expressions. Some possible extensions of the formula are presented.

AN OPPORTUNITY-BASED AGE REPLACEMENT POLICY CONSIDERING WARRANTY

1999 ◽  
Vol 06 (03) ◽  
pp. 229-236 ◽  
Author(s):  
BERMAWI P. ISKANDAR ◽  
HIROAKI SANDOH
Keyword(s):  
Time Distribution ◽  
Failure Time ◽  
Sufficient Conditions ◽  
Replacement Policy ◽  
Minimal Repair ◽  
Failure Time Distribution ◽  
Warranty Period ◽  
Preventive Replacement ◽  
Long Run ◽  
Age Replacement

This study discusses an opportunity-based age replacement policy for a system which has a warranty period (0, S]. When the system fails at its age x≤S, a minimal repair is performed. If an opportunity occurs to the system at its age x for S<x<T, we take the opportunity with probability p to preventively replace the system, while we conduct a corrective replacement when it fails on (S, T). Finally if its age reaches T, we execute a preventive replacement. Under this replacement policy, the design variable is T. For the case where opportunities occur according to a Poisson process, a long-run average cost of this policy is formulated under a general failure time distribution. It is, then, shown that one of the sufficient conditions where a unique finite optimal T* exists is that the failure time distribution is IFR (Increasing Failure Rate). Numerical examples are also presented for the Weibull failure time distribution.

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