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The purpose of this paper is to develop a preventive maintenance policy with continuous monitoring for a circular consecutive-k-out-of-n: F systems. A preventive maintenance policy is developed based on the system critical condition which is related to the number of working components in the minimal cut sets of the system. If there is at least one minimal cut set which consists of only one working component, the system is maintained preventively (PM) after a certain time interval and the failed components are replaced with the new ones to prevent the system failures. If the system fails prior to the preventive maintenance, the system is correctively maintained (CM) immediately by replacing the failed components.

The mathematical function of the expected cost rate for the proposed maintenance policy is derived. The costs of PM, CM, and replacement per component are considered. The optimal maintenance parameter, which is the PM interval, is obtained by enumeration, and the numerical studies are shown with various system and cost parameters. The performance of the proposed policy is evaluated by comparing its expected cost rate to those of the no-PM and age-PM policies. The percentage of cost increase from the no-PM and age-PM policies to the proposed PM policy is calculated and this value can represents how important the continuous monitoring in this policy.

The proposed policy outperforms other policies. When the cost of CM is high and the cost of PM is low, the proposed PM policy is more suitable.

The system consists of identical components and the component failure times follow an exponential distribution. Continuous monitoring is considered, which means that the component states can be known at any time. Three cost parameters, cost of PM, CM, and replacement per component, are considered.

This paper shows a maintenance problem for circular consecutive-k-out-of-n: F systems. Many studies on this system type focused on the reliability estimation or system design problem. Previous study with this policy (Endharta and Yun, 2015) has been developed for linear systems, although the study used a simulation approach to estimate the expected cost rate. Also, Endharta et al. (2016) considered a similar method for the different types of system, which is linear consecutive-k-out-of-n: F system.

The paper aims to present acceptance sampling plans based on failure‐censored step‐stress accelerated life tests for items having Weibull lives.

The model parameters are estimated by the method of maximum likelihood. Based on asymptotic distribution theory, the sample size and the acceptability constant are determined satisfying the producer's and consumer's risks. The step‐stress accelerated life test is optimized to have a minimum sample size by minimizing the asymptotic variance of test statistic. Two modes of step‐stress accelerated life test are considered, and a comparison between them is made. The proposed sampling plans are compared with the sampling plans based on constant stress accelerated life tests.

Asymptotic variance is a dominating factor in determining the sample size required for a sampling plan to determine the acceptability of a lot. The sample size is minimized by optimally designing a step‐stress accelerated life test so that the asymptotic variance is minimized.

The sampling plans presented in this paper are particularly useful when items to be tested are so reliable and are useful to reliability engineers and life test planners.

The weapon system of The Navy is the small quantity producing system on multiple kinds. It is consisted of various equipment and the subordinate parts of those which can repair the damaged part. The operating procedure concerning warship's repair parts managed under these systems is as follows. Firstly, if demand of repair parts occurs from warship which is the operating unit of weapon, then the Fleet(the repair & supply support battalion) is in charge of dealing with these requests. If certain request from warship is beyond the battalion's capability, it is delivered directly to the Logistic Command. In short, the repair and supply support system of repair parts can be described as the multi-level support system. The various theoretical researches on inventory management of Navy's repair parts and simulation study that reflects reality in detail have been carried out simultaneously. However, the majority of existing research has been conducted on aircraft and tank's repairable items, in that, the studies is woefully deficient in the area concerning Navy's inventory management. For that reason, this paper firstly constructs the model of consumable items that is frequently damaged reflecting characteristics of navy's repair parts inventory management using ARENA simulation. After that, this paper is trying to propose methodology to analyze optimal inventory level of each supply unit through OptQuest, the optimization program of ARENA simulation.

This paper considers and discusses analytically the optimal preventive maintenance (PM) policies of aged plants such as fossil‐fired power plants.

Shocks are assumed to occur at a nonhomogeneous Poisson process and the total damage due to each shock is additive. The system undergoes the PM at a certain time or the total damage exceeds a managerial level. The expected cost rate until PM is derived and optimal policies which minimizes it are discussed.

There exists a unique optimal time (T*) or managerial level (k*) which minimizes the expected cost rate. But there does not exist a positive pair (T*, k*), simultaneously.

The damage occurrence distribution is assumed to be nonhomogeneous Poisson one.

Useful methods to consider the optimal PM policies for power plant engineers.

This paper contributes to users of aged power plants economically and practically.

This paper proposes a new approach source node exclusion method (SNEM) to evaluate terminal pair reliability of complex communication networks.

The proposed approach breaks a non‐series‐parallel network to obtain its sub‐networks by excluding the source node from rest of the network. The reliabilities of these sub‐networks are thereafter computed by first applying the series‐parallel‐reductions to it and if any sub‐network results into another non‐series‐parallel network then it is solved by the recursive application of SNEM.

The proposed method has been applied on a variety of network and found to be quite simple, robust, and fast for terminal pair reliability evaluation of large and complex networks.

The proposed approach is quite simple in application and applicable to any general networks, i.e. directed and undirected. The method does not require any prior information such as path (or cut) sets of the network and their pre‐processing thereafter or perform complex tests on networks to match a predefined criterion.

The proposed approach provides an easy to develop and easy to use tool to determine terminal pair reliability of a communication network. The approach is particularly useful for communication network designer and analysts.

An optimization problem to obtain the optimal replacement interval is studied. The system is minimally repaired at failure and is replaced by a new one at age T. The model assumes that the time horizon associated with the number of replacements is random. The total expected cost is calculated, and the optimal replacement interval minimizing the cost is found. A numerical example is used to compare the costs associated with an infinite time line and a random time line, which this model used.

The aim of this paper is to propose a software reliability growth model based on stochastic differential equations for the integration testing phase of distributed development environment.

A client/server system (CSS), which is a new development method, has come into existence as a result of the progress of networking technology by UNIX systems. On the other hand, the effective testing method for distributed development environment has only a few presented. The method of software reliability assessment considering the interaction among software components in a distributed one is discussed.

Conventional software reliability growth models for system testing phase in distributed development environment have included many unknown parameters. Especially, the effective estimation method in terms of these unknown parameters, which means the proportion of the total testing‐load for the software component, has never been presented. This software reliability growth model can be easily applied in distributed software development, because the model has a simple structure.

This model is very useful for software developers in terms of practical reliability assessment in the actual distributed development environment.

The method of software reliability assessment considering the interaction among software components in distributed development environment is proposed. Additionally, several numerical examples for the actual data are presented.

Cox’s proportional hazards model (PHM) has been widely applied to the analysis of lifetime data. It involves covariates influencing the failure of products. Regarding the covariates as discrete random variables, the probability model is reduced to a mixture of PHM. This article presents a statistical procedure to estimate model parameters in the mixture of PHM. The estimation procedure is developed in a parametric framework when not only complete sets of field data but also incomplete ones are given. The expectation‐maximization algorithm is employed to handle the incomplete data problem. Simulation results are presented to illustrate the accuracy and some properties of the estimation results.

A random shock model for a system whose state deteriorates continuously is introduced and stochastically analyzed. It is assumed in the model that the state of the system follows a Brownian motion with negative drift and is also subject to random shocks. A repairman arrives at the system according to a Poisson process and repairs the system if the state has been below a threshold since the last repair.

Kolmogorov's forward differential equation is adopted together with a renewal argument to analyze the model stochastically. The renewal reward theorem is used to obtain the long‐run average cost per unit time.

An explicit expression is deduced for the stationary distribution of the state of the system. After assigning several costs to the system, an optimization is also studied as an example.

The present model can be used to manage a complex system whose state deteriorates both continuously and jumpwise due to the continuous wear and random shocks, such as a machine and a production line in a factory. The model can also be applied to an inventory which supplies the stock both continuously and jumpwise, such as a gas station and the distribution center for a franchise, if the continuous wear and random shocks are considered as demands for the stock.

The present model is quite complicate, however, more realistic than the previous models where the state of the system is subject to either one of continuous wear and random shocks.