Coherent systems based on sequential order statistics

The sequential order statistics (SOS) are a good way to model the lifetimes of the components in a system when the failure of a component at time t affects the performance of the working components at this age t. In this article, we study properties of the lifetimes of the coherent systems obtained using SOS. Specifically, we obtain a mixture representation based on the signature of the system. This representation is used to obtain stochastic comparisons. To get these comparisons, we obtain some ordering properties for the SOS, which in this context represent the lifetimes of k‐out‐of‐n systems. In particular, we show that they are not necessarily hazard rate ordered. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

Tail hazard rate ordering properties of order statistics and coherent systems

We study tail hazard rate ordering properties of coherent systems using the representation of the distribution of a coherent system as a mixture of the distributions of the series systems obtained from its path sets. Also some ordering properties are obtained for order statistics which, in this context, represent the lifetimes of k‐out‐of‐n systems. We pay special attention to systems with components satisfying the proportional hazard rate model or with exponential, Weibull and Pareto type II distributions. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

On matched active redundancy allocation for coherent systems with statistically dependent component lifetimes

This study addresses the allocation of matched active redundancy components to coherent systems with base components having statistically dependent lifetimes. We consider base component lifetimes and redundancy component lifetimes which are both stochastic arrangement monotone with respect to a pair of components given the lifetimes of the other components. In this context, allocating a more reliable redundancy component to the weaker base component is shown to incur a stochastically larger system lifetime. Numerical examples are presented as an illustration of the theoretical results.     

On the availability of R out of N repairable systems

An R out of N repairable system consisting of N components and operates if at least R components are functioning. Repairable means that failed components are repaired, and upon repair completion they are as good as new. We derive formulas for the expected up‐time, expected down‐time, and the availability of the system, using Markov renewal processes. We assume that either the repair times of the components are generally distributed and the components' lifetimes are exponential or vice versa. The analysis is done for systems with either cold or warm stand‐by. Numerical examples are given for several life time and repair time distributions. © 2002 Wiley Periodicals, Inc. Naval Research Logistics 49: 483–498, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/nav.10025     

On allocating one active redundancy to coherent systems with dependent and heterogeneous components' lifetimes

This article studies coherent systems of heterogenous and statistically dependent components' lifetimes. We present a sufficient and necessary condition for a stochastically longer system lifetime resulted by allocating a single active redundancy. For exchangeable components' lifetimes, allocating the redundancy to the component with more minimal path sets is proved to produce a more reliable system, and for systems with stochastic arrangement increasing components' lifetimes and symmetric structure with respect to two components, allocating the redundancy to the weaker one brings forth a larger reliability. Several numerical examples are presented to illustrate the theoretical results as well. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 335–345, 2016     

Failure profiles of coherent systems

In this paper we first introduce and study the notion of failure profiles which is based on the concepts of paths and cuts in system reliability. The relationship of failure profiles to two notions of component importance is highlighted, and an expression for the density function of the lifetime of a coherent system, with independent and not necessarily identical component lifetimes, is derived. We then demonstrate the way that failure profiles can be used to establish likelihood ratio orderings of lifetimes of two systems. Finally we use failure profiles to obtain bounds, in the likelihood ratio sense, on the lifetimes of coherent systems with independent and not necessarily identical component lifetimes. The bounds are relatively easy to compute and use. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004     

Stochastic framework for partially degradation systems with continuous component degradation‐rate‐interactions

Many conventional models that characterize the reliability of multicomponent systems are developed on the premise that for a given system, the failures of its components are independent. Although this facilitates mathematical tractability, it may constitute a significant departure from what really takes place. In many real‐world applications, system components exhibit various degrees of interdependencies, which present significant challenges in predicting degradation performance and the remaining lifetimes of the individual components as well as the system at large. We focus on modeling the performance of interdependent components of networked systems that exhibit interactive degradation processes. Specifically, we focus on how the performance level of one component affects the degradation rates of other dependent components. This is achieved by using stochastic models to characterize how degradation‐based sensor signals associated with the components evolve over time. We consider “Continuous‐Type” component interactions that occur continuously over time. This type of degradation interaction exists in many applications, in which interdependencies occur on a continuum. We use a system of stochastic differential equations to capture such “Continuous‐Type” interaction. In addition, we utilize a Bayesian approach to update the proposed model using real‐time sensor signals observed in the field and provide more accurate estimation of component residual lifetimes. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 286–303, 2014     

Replacing nonidentical vital components to extend system life

We consider a system that depends on a single vital component. If this component fails, the system life will terminate. If the component is replaced before its failure then the system life may be extended; however, there are only a finite number of spare components. In addition, the lifetimes of these spare components are not necessarily identically distributed. We propose a model for scheduling component replacements so as to maximize the expected system survival. We find the counterintuitive result that when comparing components' general lifetime distributions based on stochastic orderings, not even the strongest ordering provides an a priori guarantee of the optimal sequencing of components. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Systems composed of two types of nonidentical and dependent components

A coherent system of order n that consists two different types of dependent components is considered. The lifetimes of the components in each group are assumed to follow an exchangeable joint distribution, and the two random vectors, which represent the lifetimes of the components in each group are also assumed to be dependent. Under this particular form of dependence, all components are assumed to be dependent but they are categorized with respect to their reliability functions. Mixture representation is obtained for the survival function of the system's lifetime. Mixture representations are also obtained for the series and parallel systems consisting of disjoint modules such that all components of Type I are involved in one module (subsystem) and all components of Type II are placed in the other module. The theoretical results are illustrated with examples. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 388–394, 2015     

Reliability and mean residual life functions of coherent systems in an active redundancy

In this article, the reliability and the mean residual life (MRL) functions of a system with active redundancies at the component and system levels are investigated. In active redundancy at the component level, the original and redundant components are working together and lifetime of the system is determined by the maximum of lifetime of the original components and their spares. In the active redundancy at the system level, the system has a spare, and the original and redundant systems work together. The lifetime of such a system is then the maximum of lifetimes of the system and its spare. The lifetimes of the original component and the spare are assumed to be dependent random variables. © 2017 Wiley Periodicals, Inc. Naval Research Logistics, 64: 19–28, 2017     

A general model of heterogeneous system lifetimes and conditions for system burn‐in

Burn‐in is a technique to enhance reliability by eliminating weak items from a population of items having heterogeneous lifetimes. System burn‐in can improve system reliability, but the conditions for system burn‐in to be performed after component burn‐in remain a little understood mathematical challenge. To derive such conditions, we first introduce a general model of heterogeneous system lifetimes, in which the component burn‐in information and assembly problems are related to the prediction of system burn‐in. Many existing system burn‐in models become special cases and two important results are identified. First, heterogeneous system lifetimes can be understood naturally as a consequence of heterogeneous component lifetimes and heterogeneous assembly quality. Second, system burn‐in is effective if assembly quality variation in the components and connections which are arranged in series is greater than a threshold, where the threshold depends on the system structure and component failure rates. © 2003 Wiley Periodicals, Inc. Naval Research Logistics 50: 364–380, 2003.     

A note on necessary and sufficient conditions for ordering properties of coherent systems with exchangeable components

We give necessary and sufficient conditions based on signatures to obtain distribution‐free stochastic ordering properties for coherent systems with exchangeable components. Specifically, we consider the stochastic, the hazard (failure) rate, the reversed hazard rate, and the likelihood ratio orders. We apply these results to obtain stochastic ordering properties for all the coherent systems with five or less exchangeable components. Our results extend some preceding results. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011     

A note on signature‐based expressions for the entropy of mixed r‐out‐of‐ n systems

We provide an expression for the Shannon entropy of mixed r‐out‐of‐ n systems when the lifetimes of the components are independent and identically distributed. The expression gives the system's entropy in terms of the system signature, the distribution and density functions of the lifetime model, and the information measures of the beta distribution. Bounds for the system's entropy are obtained by direct applications of the concavity of the entropy and the information inequality.Copyright © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 202–206, 2014     

Parametric inference for component distributions from lifetimes of systems with dependent components

In system reliability analysis, for an n ‐component system, the estimation of the performance of the components in the system is not straightforward in practice, especially when the components are dependent. Here, by assuming the n components in the system to be identically distributed with a common distribution belonging to a scale‐family and the dependence structure between the components being known, we discuss the estimation of the lifetime distributions of the components in the system based on the lifetimes of systems with the same structure. We develop a general framework for inference on the scale parameter of the component lifetime distribution. Specifically, the method of moments estimator (MME) and the maximum likelihood estimator (MLE) are derived for the scale parameter, and the conditions for the existence of the MLE are also discussed. The asymptotic confidence intervals for the scale parameter are also developed based on the MME and the MLE. General simulation procedures for the system lifetime under this model are described. Finally, some examples of two‐ and three‐component systems are presented to illustrate all the inferential procedures developed here. © 2012 Wiley Periodicals, Inc. Naval Research Logistics, 2012     

On the application and extension of system signatures in engineering reliability

Following a review of the basic ideas in structural reliability, including signature‐based representation and preservation theorems for systems whose components have independent and identically distributed (i.i.d.) lifetimes, extensions that apply to the comparison of coherent systems of different sizes, and stochastic mixtures of them, are obtained. It is then shown that these results may be extended to vectors of exchangeable random lifetimes. In particular, for arbitrary systems of sizes m < n with exchangeable component lifetimes, it is shown that the distribution of an m‐component system's lifetime can be written as a mixture of the distributions of k‐out‐of‐n systems. When the system has n components, the vector of coefficients in this mixture representation is precisely the signature of the system defined in Samaniego, IEEE Trans Reliabil R–34 (1985) 69–72. These mixture representations are then used to obtain new stochastic ordering properties for coherent or mixed systems of different sizes. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

The joint signature of coherent systems

We investigate the joint signature of $m$ coherent systems, under the assumption that the components have independent and identically distributed lifetimes. The joint signature, for a particular ordering of failure times, is an $m$‐dimensional matrix depending solely on the composition of the systems and independent of the underlying distribution function of the component lifetimes. The elements of the $m$‐dimensional matrix are formulated based on the joint signatures of numerous series of parallel systems. The number of the joint signatures involved is an exponential function of the number of the minimal cut sets of each original system and may, therefore, be significantly large. We prove that although this number is typically large, a great number of the joint signatures are repeated, or removed by negative signs. We determine the maximum number of different joint signatures based on the number of systems and components. It is independent of the number of the minimal cut sets of each system and is polynomial in the number of components. Moreover, we consider all permutations of failure times and demonstrate that the results for one permutation can be of use for the others. Our theorems are applied to various examples. The main conclusion is that the joint signature can be computed much faster than expected.     

On lifetimes in random environments

For a component operating in random environment, whose hazard rate is assumed to be the realization of a suitable increasing stochastic process, conditions are found such that its lifetime is increasing in likelihood ratio (ILR). For the lifetimes of two components of the same kind some comparisons based on partial stochastic orders are presented. Some applications to the case of repairable components are finally provided. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 365–375, 1998     

Bayesian inference based on partial monitoring of components with applications to preventive system maintenance

Consider a binary, monotone system of n components. The assessment of the parameter vector, θ, of the joint distribution of the lifetimes of the components and hence of the reliability of the system is often difficult due to scarcity of data. It is therefore important to make use of all information in an efficient way. For instance, prior knowledge is often of importance and can indeed conveniently be incorporated by the Bayesian approach. It may also be important to continuously extract information from a system currently in operation. This may be useful both for decisions concerning the system in operation as well as for decisions improving the components or changing the design of similar new systems. As in Meilijson [12], life‐monitoring of some components and conditional life‐monitoring of some others is considered. In addition to data arising from this monitoring scheme, so‐called autopsy data are observed, if not censored. The probabilistic structure underlying this kind of data is described, and basic likelihood formulae are arrived at. A thorough discussion of an important aspect of this probabilistic structure, the inspection strategy, is given. Based on a version of this strategy a procedure for preventive system maintenance is developed and a detailed application to a network system presented. All the way a Bayesian approach to estimation of θ is applied. For the special case where components are conditionally independent given θ with exponentially distributed lifetimes it is shown that the weighted sum of products of generalized gamma distributions, as introduced in Gåsemyr and Natvig [7], is the conjugate prior for θ. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 551–577, 2001.     

Some comparisons of residual life of coherent systems with exchangeable components

Most of the research, on the study of the reliability properties of technical systems, assume that the components of the system operate independently. However, in real life situation, it is more reasonable to assume that there is dependency among the components of the system. In this article, we give sufficient conditions based on the signature and the joint distribution of component lifetimes to obtain stochastic ordering results for coherent and mixed systems with exchangeable components. Some stochastic orders on dynamic (or conditional) signature of coherent systems are also provided. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 549–556, 2014     

Optimal material control in an assembly system with component commonality

Allocation of scarce common components to finished product orders is central to the performance of assembly systems. Analysis of these systems is complex, however, when the product master schedule is subject to uncertainty. In this paper, we analyze the cost—service performance of a component inventory system with correlated finished product demands, where component allocation is based on a fair shares method. Such issuing policies are used commonly in practice. We quantify the impact of component stocking policies on finished product delays due to component shortages and on product order completion rates. These results are used to determine optimal base stock levels for components, subject to constraints on finished product service (order completion rates). Our methodology can help managers of assembly systems to (1) understand the impact of their inventory management decisions on customer service, (2) achieve cost reductions by optimizing their inventory investments, and (3) evaluate supplier performance and negotiate contracts by quantifying the effect of delivery lead times on costs and customer service. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48:409–429, 2001