Reliability Analysis of Repairable Systems Using Stochastic Point Processes

In order to analyze the failure data from repairable systems, the homogeneous Poisson process (HPP) is usually used. In general, HPP cannot be applied to analyze the entire life cycle of a complex, re-pairable system because the rate of occurrence of failures (ROCOF) of the system changes over time rather than remains stable. However, from a practical point of view, it is always preferred to apply the simplest method to address problems and to obtain useful practical results. Therefore, we attempted to use the HPP model to analyze the failure data from real repairable systems. A graphic method and the Laplace test were also used in the analysis. Results of numerical applications show that the HPP model may be a useful tool for the entire life cycle of repairable systems.

Nonlinear Mixed-Effects Models for Repairable Systems Reliability

Mixed-effects models,also called random-effects models,are a regression type of analysis which enables the analyst to not only describe the trend over time within each subject,but also to describe the variation among different subjects.Nonlinear mixed-effects models provide a powerful and flexible tool for handling the unbalanced count data.In this paper,nonlinear mixed-effects models are used to analyze the failure data from a repairable system with multiple copies.By using this type of models,statistical inferences about the population and all copies can be made when accounting for copy-to-copy variance.Results of fitting nonlinear mixed-effects models to nine failure-data sets show that the nonlinear mixed-effects models provide a useful tool for analyzing the failure data from multi-copy repairable systems.

Reliability Analysis of Some Typical Repairable Systems with Arbitrary Repair-Time Distribution

In this paper, reliability of some typical non-Markov repairable systems, including series systems, m-out-of- n or majority vote systems, and n : m cross-strapping standby redundant systems with general repair-time distribution, are studied by applying the generalized Markov renewal process (GMRP). The stochastic behavior of the typical systems is analyzed here. Formulas for mean time to first system failure, MTBF, MTTR, and availability are then developed.

Uncertain multiobjective redundancy allocation problem of repairable systems based on artificial bee colony algorithm

Based on the uncertainty theory, this paper is devoted to the redundancy allocation problem in repairable parallel-series systems with uncertain factors, where the failure rate, repair rate and other relative coefficients involved are considered as uncertain variables. The availability of the system and the corresponding designing cost are considered as two optimization objectives. A crisp multiobjective optimization formulation is presented on the basis of uncertainty theory to solve this resultant problem. For solving this problem efficiently, a new multiobjective artificial bee colony algorithm is proposed to search the Pareto efficient set, which introduces rank value and crowding distance in the greedy selection strategy, applies fast non-dominated sort procedure in the exploitation search and inserts tournament selection in the onlooker bee phase. It shows that the proposed algorithm outperforms NSGA-II greatly and can solve multiobjective redundancy allocation problem efficiently. Finally, a numerical example is provided to illustrate this approach.

APPROXIMATING ANALYSIS OF A KIND OF REPAIRABLE STANDBY SYSTEMS

In this paper, some approximating analyses are considered in a class of repairable systems.By using the properties and the techniques of partial orderings for random variables, we find some conditions under which some reliability indices of a system are less (or larger) than the corresponding indices of another system; and then, we obtain the bounds of the main reliability indices of a general system.

Arithmetic Reduction of Intensity or Age Models with Bathtub Failure Intensity

In this paper, the authors will study the estimation of maintenance efficiency in Arithmetic Reduction of Intensity （ARI） and Arithmetic Reduction of Age （ARA） models with a memory m. These models have been proposed by Doyen （2005）, the failure process is simply Non Homogeneous Poisson Process （NHPP）. Our models are defined by reformulation of ARI and ARA ones using bathtub failure intensity. This form is presented like a superposition of two NHPP and Homogeneous Poisson Process （HPP）. Moreover, the particularity of this model allows taking account of system state improvement in time course. The maintenance effect is characterized by the change induced on the failure intensity before and after failure during degradation period. To simplify study, the asymptotic properties of failure process are derived. Then, the asymptotic normality of several maintenance efficiency estimators can be proved in the case where the failure process without maintenance is known. Practically, the coverage rate of the asymptotic confidence intervals issued from those estimators is studied.

AVAILABILITY ANALYSIS OF THE QUEUEING SYSTEM GI/PH/I WITH SERVER BREAKDOWNS

In the existing literature of Repairable Queueing Systems (RQS), i.e., queueing systems with server breakdowns, it is almost all assumed that interarrival times of successive customers are independent, identically exponentially distributed. In this paper, we deal with more generic system GI/PH/1 with server's exponential uptime and phase-type repair time. With matrix analysis theory, we establish the equilibrium condition and the characteristics of the system, derive the transient and stationary availability behavior of the system.