A review of multi-component maintenance models with economic dependence

In this paper we review the literature on multi-component maintenance models with economic dependence. The emphasis is on papers that appeared after 1991, but there is an overlap with Section 2 of the most recent review paper by Cho and Parlar (1991). We distinguish between stationary models, where a long-term stable situation is assumed, and dynamic models, which can take information into account that becomes available only on the short term. Within the stationary models we choose a classification scheme that is primarily based on the various options of grouping maintenance activities: grouping either corrective or preventive maintenance, or combining preventive-maintenance actions with corrective actions. As such, this classification links up with the possibilities for grouped maintenance activities that exist in practice

Transient Analysis of a Two-Unit Standby System with Markovian Degrading Units

A two-unit cold standby system with Markovian degrading units and one repair facility is considered. Two types of repair are possible: preventive and corrective, where the latter is supposed to be more time consuming than the first. The system is controlled by a repair policy of control limit type: a preventive repair on the working unit is carried out as soon as the state of this unit exceeds a certain threshold unless the repair facility is occupied by the other unit. In this paper we derive explicit expressions for the Laplace transforms of the up- and down-periods of this system, which provide insight in the availability of the system and which can be used to obtain approximations for the interval availability distribution. An iterative numerical procedure is presented for the special case of generalized Erlangian distributed repair times.repairable systems, single repair facility, preventive maintenance, corrective maintenance, cold standby, Markovian degradation, transient behavior, interval availability

A note on exponential dispersion models which are invariant under length-biased sampling

Length-biased sampling (LBS) situations may occur in clinical trials, reliability, queueing models, survival analysis and population studies where a proper sampling frame is absent. In such situations items are sampled at rate proportional to their "length" so that larger values of the quantity being measured are sampled with higher probabilities. More specifically, if f(x) is a p.d.f. presenting a parent population composed of non-negative valued items then the sample is practically drawn from a distribution with p.d.f. g(x)=xf(x)/E(X) describing the length-biased population. In this case the distribution associated with g is termed a length-biased distribution. In this note, we present a unified approach for characterizing exponential dispersion models which are invariant, up to translations, under various types of LBS. The approach is rather simple as it reduces such invariance problems into differential equations in terms of the derivatives of the associated variance functions.Exponential dispersion model Length-biased sampling Variance function

Group Testing Models with Processing Times and Incomplete Identification

We consider the group testing problem for a nite population of possibly defective items with the objective of sampling a prespeci ed demanded number of nondefective items at minimum cost. Group testing means that items can be pooled and tested together; if the group comes out clean, all items in it are nondefective, while a \contaminated " group is scrapped. Every test takes a random amount of time and a given deadline has to be met. If the prescribed number of nondefective items is not reached, the demand has to be satis ed at a higher (penalty) cost. We derive explicit formulas for the distributions underlying the cost functionals of this model. It is shown in numerical examples that these results can be used to determine the optimal group size

Two-stage queueing network models for quality control and testing

We study sojourn times in a two-node open queueing network with a processor sharing node and a delay node, with Poisson arrivals at the PS node. Motivated by quality control and blood testing applications, we consider a feedback mechanism in which customers may either leave the system after service at the PS node or move to the delay node; from the delay node, they always return to the PS node for new quality controls or blood tests. We propose various approximations for the distribution of the total sojourn time in the network; each of these approximations yields the exact mean sojourn time, and very accurate results for the variance. The best of the three approximations is used to tackle an optimization problem that is mainly inspired by a blood testing application.Queueing Sojourn time Feedback Blood testing