International Journal of Reliability, Quality and Safety Engineering

This paper proposes two modified replacement policies which combine random replacement with standard age and periodic policies, where units undergo replacement at the first completion of some random working time over a planned time T, which are called replacement overtime. The expected cost rates of age and periodic replacement overtime polices are obtained, and optimal policies which minimize them are discussed analytically. Comparisons between such two overtime policies and standard age and periodic replacements are made in detail. When two costs for replacement overtime and standard age or periodic policies are the same, it is shown as estimated previously that the standard replacements are better than their overtime policies. Furthermore, two modified replacement overtime costs are discussed and computed numerically when such new policies would be better than the standard age and periodic replacements.

Some systems work for a job with random working and processing times, and are checked at periodic and random times. When a failure occurs, we execute the backup operation to the latest checking time. First, the expected costs with periodic and random backups are formulated, and comparisons between periodic and random policies are made. Next, we focus on the backup policies when the system is checked at the Nth interval of working times, two total expected costs are obtained and optimal numbers N* which minimize them are derived analytically. Finally, one modified backup model in which failures are detected only at checking times is proposed and two expected costs are obtained.

In this paper, we consider an interval estimation of the age replacement problem, where the underlying failure time probability is given by the two-parameter Weibull distribution. The parametric bootstrap is used to obtain the probability distribution of an estimator for the optimal age replacement time minimizing the expected cost per unit time in the steady state. We focus on both cases with complete and incomplete samples of failure time data, and calculate not only the higher moments of an estimator for the optimal age replacement time but also the confidence interval.

We discuss software hazard rate modeling with a change of testing-environment and a software reliability assessment method based on the proposed software hazard rate models. A software hazard rate model is known as one of the important and useful mathematical models for describing the software failure-occurrence phenomenon and conducting quantitative software reliability assessment. Taking into consideration of the effect of the change in software reliability growth modeling is expected to conduct more accurate software reliability assessment because it is said that such approach enables us to conduct more plausible software reliability assessment reflecting the actual testing-environment. Especially in this paper, we develop exponential-type software hazard rate models with effect of change-point and a software reliability assessment method based on our models. Finally, we show numerical examples for our models and results of model comparisons with existing software hazard rate models by using actual data.

At present, a cloud computing is attracting attention as a network service to share the computing resources, i.e., networks, servers, storage, applications, and services. We focus on a cloud computing environment by using open source software such as OpenStack and Eucalyptus because of the unification management of data and low cost. In this paper, we propose a new approach to software dependability assessment based on stochastic differential equation modeling in order to consider the interesting aspect of the numbers of components, cloud applications, and users. Also, we analyze actual data to show numerical examples of software dependability assessment considering such characteristics of cloud computing. Moreover, we discuss the determination of optimum software maintenance times minimizing the total expected software cost.

A comparison study in basic preventive replacement (PR) policies based on a cumulative damage model is done. Three well-known PR policies (time-based, shock number-based, cumulative damage-based policies) are considered and the expected cost rate is used as the objective function to determine the optimal policy. Each policy requires certain information in the cumulative damage model. We evaluate the expected values of information by numerical examples and investigate the effect of model parameters and cost terms on the optimal expected cost rate. A damage-based replacement policy with periodic inspection is also proposed and compared with the three PR policies by numerical examples.