The failure probability of components in three-state networks with applications to age replacement policy

2017 ◽  
Vol 54 (4) ◽  
pp. 1051-1070 ◽  
Author(s):  
S. Ashrafi ◽  
M. Asadi
Keyword(s):  
Failure Probability ◽  
The State ◽  
Replacement Policy ◽  
Two Dimensional ◽  
Age Replacement ◽  
Stochastic Properties ◽  
Failure Probabilities

Abstract In this paper we investigate the stochastic properties of the number of failed components of a three-state network. We consider a network made up of n components which is designed for a specific purpose according to the performance of its components. The network starts operating at time t = 0 and it is assumed that, at any time t > 0, it can be in one of states up, partial performance, or down. We further suppose that the state of the network is inspected at two time instants t1 and t2 (t1 < t2). Using the notion of the two-dimensional signature, the probability of the number of failed components of the network is calculated, at t1 and t2, under several scenarios about the states of the network. Stochastic and ageing properties of the proposed failure probabilities are studied under different conditions. We present some optimal age replacement policies to show applications of the proposed criteria. Several illustrative examples are also provided.

A note on the upper bound for the optimal work size

2004 ◽  
Vol 41 (01) ◽  
pp. 277-280
Author(s):  
Ji Hwan Cha
Keyword(s):  
Upper Bound ◽  
Optimization Problem ◽  
Replacement Policy ◽  
Two Dimensional ◽  
Age Replacement ◽  
Work Size ◽  
Dimensional Optimization

Mi (2002) recently considered a two-dimensional optimization problem for the optimal age-replacement policy and the optimal work size. In order to find (y ∗,T ∗), Mi (2002) found the optimal age-replacement policy T ∗(y) for each fixed work size y, and then searched for the optimal work size y ∗. When applying this approach, for each fixed work size y, Mi (2002) obtained the bounds for T ∗(y). However, no bound for the optimal work size y ∗ was derived. In this note, the results on the upper bound for the optimal work size y ∗ are given.

A note on the upper bound for the optimal work size

2004 ◽  
Vol 41 (1) ◽  
pp. 277-280 ◽  
Author(s):  
Ji Hwan Cha
Keyword(s):  
Upper Bound ◽  
Optimization Problem ◽  
Replacement Policy ◽  
Two Dimensional ◽  
Age Replacement ◽  
Work Size ◽  
Dimensional Optimization

Mi (2002) recently considered a two-dimensional optimization problem for the optimal age-replacement policy and the optimal work size. In order to find (y∗,T∗), Mi (2002) found the optimal age-replacement policy T∗(y) for each fixed work size y, and then searched for the optimal work size y∗. When applying this approach, for each fixed work size y, Mi (2002) obtained the bounds for T∗(y). However, no bound for the optimal work size y∗ was derived. In this note, the results on the upper bound for the optimal work size y∗ are given.

On classes of life distributions based on the mean time to failure function

2021 ◽  
Vol 58 (2) ◽  
pp. 289-313
Author(s):  
Ruhul Ali Khan ◽  
Dhrubasish Bhattacharyya ◽  
Murari Mitra
Keyword(s):  
Damage Model ◽  
Replacement Policy ◽  
Time To Failure ◽  
Mean Time To Failure ◽  
Moment Convergence ◽  
Life Distributions ◽  
Cumulative Damage Model ◽  
The Mean ◽  
Age Replacement ◽  
Mean Time

AbstractThe performance and effectiveness of an age replacement policy can be assessed by its mean time to failure (MTTF) function. We develop shock model theory in different scenarios for classes of life distributions based on the MTTF function where the probabilities $\bar{P}_k$ of surviving the first k shocks are assumed to have discrete DMTTF, IMTTF and IDMTTF properties. The cumulative damage model of A-Hameed and Proschan [1] is studied in this context and analogous results are established. Weak convergence and moment convergence issues within the IDMTTF class of life distributions are explored. The preservation of the IDMTTF property under some basic reliability operations is also investigated. Finally we show that the intersection of IDMRL and IDMTTF classes contains the BFR family and establish results outlining the positions of various non-monotonic ageing classes in the hierarchy.

FORWARD APPORTIONMENT OF CENSORED COUNTS FOR DISCRETE NONPARAMETRIC MAXIMUM LIKELIHOOD ESTIMATION OF FAILURE PROBABILITIES

2009 ◽  
Vol 16 (03) ◽  
pp. 213-234
Author(s):  
MINNIE H. PATEL ◽  
H.-S. JACOB TSAO
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Closed Form ◽  
Failure Probability ◽  
Likelihood Estimation ◽  
Lifetime Distribution ◽  
Nonparametric Maximum Likelihood ◽  
Kaplan Meier ◽  
Probability Estimates ◽  
Failure Probabilities

Empirical cumulative lifetime distribution function is often required for selecting lifetime distribution. When some test items are censored from testing before failure, this function needs to be estimated, often via the approach of discrete nonparametric maximum likelihood estimation (DN-MLE). In this approach, this empirical function is expressed as a discrete set of failure-probability estimates. Kaplan and Meier used this approach and obtained a product-limit estimate for the survivor function, in terms exclusively of the hazard probabilities, and the equivalent failure-probability estimates. They cleverly expressed the likelihood function as the product of terms each of which involves only one hazard probability ease of derivation, but the estimates for failure probabilities are complex functions of hazard probabilities. Because there are no closed-form expressions for the failure probabilities, the estimates have been calculated numerically. More importantly, it has been difficult to study the behavior of the failure probability estimates, e.g., the standard errors, particularly when the sample size is not very large. This paper first derives closed-form expressions for the failure probabilities. For the special case of no censoring, the DN-MLE estimates for the failure probabilities are in closed forms and have an obvious, intuitive interpretation. However, the Kaplan–Meier failure-probability estimates for cases involving censored data defy interpretation and intuition. This paper then develops a simple algorithm that not only produces these estimates but also provides a clear, intuitive justification for the estimates. We prove that the algorithm indeed produces the DN-MLE estimates and demonstrate numerically their equivalence to the Kaplan–Meier-based estimates. We also provide an alternative algorithm.

A weak derivative approach to optimization of threshold parameters in a multicomponent maintenance system

2001 ◽  
Vol 38 (02) ◽  
pp. 386-406 ◽  
Author(s):  
Bernd Heidergott
Keyword(s):  
Optimization Problems ◽  
Estimation Algorithm ◽  
Replacement Policy ◽  
Cost Performance ◽  
Weak Derivative ◽  
Preventive Replacement ◽  
Maintenance System ◽  
Threshold Optimization ◽  
Age Replacement ◽  
The Cost

We consider a multicomponent maintenance system controlled by an age replacement policy: when one of the components fails, it is immediately replaced; all components older than a threshold age θ are preventively replaced. Costs are associated with each maintenance action, such as replacement after failure or preventive replacement. We derive a weak derivative estimator for the derivative of the cost performance with respect to θ. The technique is quite general and can be applied to many other threshold optimization problems in maintenance. The estimator is easy to implement and considerably increases the efficiency of a Robbins-Monro type of stochastic approximation algorithm. The paper is self-contained in the sense that it includes a proof of the correctness of the weak derivative estimation algorithm.

scholarly journals Dynamic Reliability Modeling of Three-State Networks

2014 ◽  
Vol 51 (4) ◽  
pp. 999-1020 ◽  
Author(s):  
S. Ashrafi ◽  
M. Asadi
Keyword(s):  
Network Structure ◽  
Single Step ◽  
Two Dimensional ◽  
Reliability Modeling ◽  
Stochastic Orderings ◽  
Dynamic Reliability ◽  
Network States ◽  
Dynamic Signature ◽  
Stochastic Properties ◽  
Residual Lifetimes

This paper is an investigation into the reliability and stochastic properties of three-state networks. We consider a single-step network consisting of n links and we assume that the links are subject to failure. We assume that the network can be in three states, up (K = 2), partial performance (K = 1), and down (K = 0). Using the concept of the two-dimensional signature, we study the residual lifetimes of the networks under different scenarios on the states and the number of failed links of the network. In the process of doing so, we define variants of the concept of the dynamic signature in a bivariate setting. Then, we obtain signature based mixture representations of the reliability of the residual lifetimes of the network states under the condition that the network is in state K = 2 (or K = 1) and exactly k links in the network have failed. We prove preservation theorems showing that stochastic orderings and dependence between the elements of the dynamic signatures (which relies on the network structure) are preserved by the residual lifetimes of the states of the network (which relies on the network ageing). Various illustrative examples are also provided.

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