Order statistics, Poisson processes and repairable systems

1976 ◽  
Vol 13 (3) ◽  
pp. 519-529 ◽  
Author(s):  
Douglas R. Miller
Keyword(s):  
Order Statistics ◽  
Point Processes ◽  
Failure Time ◽  
Sufficient Conditions ◽  
Renewal Processes ◽  
Repairable Systems ◽  
Homogeneous Poisson Process ◽  
Necessary And Sufficient ◽  
Non Homogeneous Poisson Process ◽  
Weibull Process

Necessary and sufficient conditions are presented under which the point processes equivalent to order statistics of n i.i.d. random variables or superpositions of n i.i.d. renewal processes converge to a non-degenerate limiting process as n approaches infinity. The limiting process must be one of three types of non-homogeneous Poisson process, one of which is the Weibull process. These point processes occur as failure-time models in the reliability theory of repairable systems.

Order statistics, Poisson processes and repairable systems

1976 ◽  
Vol 13 (03) ◽  
pp. 519-529 ◽  
Author(s):  
Douglas R. Miller
Keyword(s):  
Order Statistics ◽  
Point Processes ◽  
Failure Time ◽  
Sufficient Conditions ◽  
Renewal Processes ◽  
Repairable Systems ◽  
Homogeneous Poisson Process ◽  
Necessary And Sufficient ◽  
Non Homogeneous Poisson Process ◽  
Weibull Process

Necessary and sufficient conditions are presented under which the point processes equivalent to order statistics of n i.i.d. random variables or superpositions of n i.i.d. renewal processes converge to a non-degenerate limiting process as n approaches infinity. The limiting process must be one of three types of non-homogeneous Poisson process, one of which is the Weibull process. These point processes occur as failure-time models in the reliability theory of repairable systems.

scholarly journals Testing and preventive maintenance scheduling optimization for aging systems modeled by generalized renewal process

2009 ◽  
Vol 29 (3) ◽  
pp. 563-576 ◽  
Author(s):  
Vinícius Correa Damaso ◽  
Pauli Adriano de Almada Garcia
Keyword(s):  
Poisson Process ◽  
Renewal Process ◽  
Point Processes ◽  
Water System ◽  
Actual State ◽  
Feed Water ◽  
Repairable Systems ◽  
Homogeneous Poisson Process ◽  
Availability Analysis ◽  
Non Homogeneous Poisson Process

The use of stochastic point processes to model the reliability of repairable systems has been a regular approach to establish survival measures in failure versus repair scenarios. However, the traditional processes do not consider the actual state in which an item returns to operational condition. The traditional renewal process considers an "as-good-as-new" philosophy, while a non-homogeneous Poisson process is based on the minimal repair concept. In this work, an approach based on the concept of Generalized Renewal Process (GRP) is presented, which is a generalization of the renewal process and the non-homogeneous Poisson process. A stochastic modeling is presented for systems availability analysis, including testing and/or preventive maintenances scheduling. To validate the proposed approach, it was performed a case study of a hypothetical auxiliary feed-water system of a nuclear power plant, using genetic algorithm as optimization tool.

Further results for Gauss-Poisson processes

1972 ◽  
Vol 4 (01) ◽  
pp. 151-176 ◽  
Author(s):  
R. K. Milne ◽  
M. Westcott
Keyword(s):  
Point Processes ◽  
Sufficient Conditions ◽  
Infinite Divisibility ◽  
Poisson Processes ◽  
Generating Functional ◽  
Basic Approach ◽  
New Class ◽  
Two Measures ◽  
Necessary And Sufficient ◽  
Statistical Results

Newman (1970) introduced an interesting new class of point processes which he called Gauss-Poisson. They are characterized, in the most general case, by two measures. We determine necessary and sufficient conditions on these measures for the resulting point process to be well defined, and proceed to a systematic study of its properties. These include stationarity, ergodicity, and infinite divisibility. We mention connections with other classes of point processes and some statistical results. Our basic approach is through the probability generating functional of the process.

The probability that the largest observation is censored

1993 ◽  
Vol 30 (03) ◽  
pp. 602-615 ◽  
Author(s):  
R. A. Maller ◽  
S. Zhou
Keyword(s):  
Survival Time ◽  
Failure Time ◽  
Sufficient Conditions ◽  
Random Variables ◽  
Consistent Estimator ◽  
Survival Times ◽  
Practical Difficulty ◽  
Independent Censoring ◽  
The Mean ◽  
Necessary And Sufficient

Suppose n possibly censored survival times are observed under an independent censoring model, in which the observed times are generated as the minimum of independent positive failure and censor random variables. A practical difficulty arises when the largest observation is censored since then the usual non-parametric estimator of the distribution of the survival time is improper. We calculate the probability that this occurs and give necessary and sufficient conditions for this probability to converge to 0 as n →∞. As an application, we show that if this probability is 0, asymptotically, then a consistent estimator for the mean failure time can be found. An almost sure version of the problem is also considered.

Optimum replacement of a system subject to shocks

1986 ◽  
Vol 23 (1) ◽  
pp. 107-114 ◽  
Author(s):  
Mohamed Abdel-Hameed
Keyword(s):  
Poisson Process ◽  
Sufficient Conditions ◽  
Sample Path ◽  
Cost Structure ◽  
Homogeneous Poisson Process ◽  
Jump Size ◽  
Shock Process ◽  
Finite Period ◽  
Periodic Replacement ◽  
Non Homogeneous Poisson Process

A system is subject to shocks. Each shock weakens the system and makes it more expensive to run. It is desirable to determine a replacement time for the system. Boland and Proschan [4] consider periodic replacement of the system and give sufficient conditions for the existence of an optimal finite period, assuming that the shock process is a non-homogeneous Poisson process and the cost structure does not depend on time. Block et al. [3] establish similar results assuming that cost structure is time dependent, still requiring that the shock process is a non-homogeneous Poisson process. We show via a sample path argument that the results of [3] and [4] hold for any counting process whose jump size is of one unit magnitude.

The probability that the largest observation is censored

1993 ◽  
Vol 30 (3) ◽  
pp. 602-615 ◽  
Author(s):  
R. A. Maller ◽  
S. Zhou
Keyword(s):  
Survival Time ◽  
Failure Time ◽  
Sufficient Conditions ◽  
Random Variables ◽  
Consistent Estimator ◽  
Survival Times ◽  
Practical Difficulty ◽  
Independent Censoring ◽  
The Mean ◽  
Necessary And Sufficient

Suppose n possibly censored survival times are observed under an independent censoring model, in which the observed times are generated as the minimum of independent positive failure and censor random variables. A practical difficulty arises when the largest observation is censored since then the usual non-parametric estimator of the distribution of the survival time is improper. We calculate the probability that this occurs and give necessary and sufficient conditions for this probability to converge to 0 as n →∞. As an application, we show that if this probability is 0, asymptotically, then a consistent estimator for the mean failure time can be found. An almost sure version of the problem is also considered.

On Cox processes and gamma renewal processes

1988 ◽  
Vol 25 (02) ◽  
pp. 423-427 ◽  
Author(s):  
Nikos Yannaros
Keyword(s):  
Gamma Distribution ◽  
Renewal Process ◽  
Shape Parameter ◽  
Sufficient Conditions ◽  
Short Description ◽  
Necessary And Sufficient Conditions ◽  
Renewal Processes ◽  
Cox Process ◽  
Cox Processes ◽  
Necessary And Sufficient

It is shown that the gamma distribution with shape parameter α can be obtained through a p-thinning for every 0 < p < 1, when 0 < α ≦ 1. In the case α > 1, the gamma distribution cannot be obtained through thinning. The class of renewal processes with gamma-distributed times between events is considered. It is shown that an ordinary gamma renewal process is a Cox process if and only if 0 < α ≦ 1. Necessary and sufficient conditions for delayed gamma renewal processes to be Cox are also given. Finally, a short description of the gamma renewal process as a Cox process is given.

A note on exceedances and rare events of non-stationary sequences

1993 ◽  
Vol 30 (04) ◽  
pp. 877-888 ◽  
Author(s):  
J. Hüsler
Keyword(s):  
Point Process ◽  
Point Processes ◽  
Rare Events ◽  
Sufficient Conditions ◽  
Stationary Sequence ◽  
Poisson Processes ◽  
Regularity Conditions ◽  
Mixing Conditions ◽  
Necessary And Sufficient ◽  
Point Process Of Exceedances

Exceedances of a non-stationary sequence above a boundary define certain point processes, which converge in distribution under mild mixing conditions to Poisson processes. We investigate necessary and sufficient conditions for the convergence of the point process of exceedances, the point process of upcrossings and the point process of clusters of exceedances. Smooth regularity conditions, as smooth oscillation of the non-stationary sequence, imply that these point processes converge to the same Poisson process. Since exceedances are asymptotically rare, the results are extended to triangular arrays of rare events.

Limit laws for kth order statistics from strong-mixing processes

1984 ◽  
Vol 21 (04) ◽  
pp. 720-729 ◽  
Author(s):  
W. Dziubdziela
Keyword(s):  
Weak Convergence ◽  
Order Statistics ◽  
Poisson Distribution ◽  
Sufficient Conditions ◽  
Strong Mixing ◽  
Mixing Processes ◽  
Limit Laws ◽  
Independent Case ◽  
Necessary And Sufficient ◽  
Mixing Sequence

We present necessary and sufficient conditions for the weak convergence of the distributions of the kth order statistics from a strictly stationary strong-mixing sequence of random variables to limit laws which are represented in terms of a compound Poisson distribution. The obtained limit laws form a class larger than that occurring in the independent case.

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