Generalized Reliability Analysis of Mechanical Systems with Imperfect Maintenance

Generalized reliability models and failure rate models of mechanical systems are developed in this paper according to the system working mechanism, which take the design parameters as input. The models consider strength degradation and imperfect maintenance. Besides, the models take into account the failure correlation caused by homologous load effect and the maintenance correlation owing to group maintenance. Unlike traditional reliability models, the models do not rely on empirical assumptions when considering failure correlation and maintenance correlation and have clear physical meaning. Moreover, the correctness and effectiveness of the models are verified by Monte Carlo simulations. Finally, the influences of failure correlation and maintenance correlation on generalized reliability, the influences of failure correlation on maintenance correlation, and the influences of maintenance correlation on failure correlation are analyzed via numerical examples. The results show that failure correlation and maintenance correlation have great influences on generalized reliability, and the interaction between the two correlation shows obvious time-varying characteristics.

Assessment of time-dependent structural resistance of RC bridges in the Barak valley region, Assam, India

The reinforced concrete (RC) bridges deteriorate essentially due to strength loss induced by aging of the structure, extreme weathering conditions, and unplanned increased service loads. However, these load variations and aging factors equally could compromise structural reliability, and service life for continuous satisfactory operation of service bridges for future performance. A reasonable model of bridge strength and applied loads becomes the basis of accurate prediction of bridge functionality. Hence, time-dependent reliability approaches could be used efficiently to gain a reliable understanding of issues facing by the bridges in the study area for appropriate solutions. In this paper, the reliability of bridges under harsh conditions studied using time-variant and time-invariant reliability models in which both load and resistance considered as a time-dependent parameter. A combination of condition rating (CR) and time-dependent load employed to attain accurate insights about the degradation of structural resistance of the existing bridges. The result shows the significant impact of aging as well as traffic loads influence in the service life of both national highways (NH) and rural road service bridges. These observations might be used to adopt appropriate planning strategies as well as rational decisions to ensure the safety of the bridges for future operation.

A study on stochastic modelling of the repairable system

All reliability models consisting of random time factors form stochastic processes. In this paper we recall the definitions of the most common point processes which are used for modelling of repairable systems. Particularly this paper presents stochastic processes as examples of reliability systems for the support of the maintenance related decisions. We consider the simplest one-unit system with a negligible repair or replacement time, i.e., the unit is operating and is repaired or replaced at failure, where the time required for repair and replacement is negligible.When the repair or replacement is completed, the unit becomes as good as new and resumes operation. The stochastic modelling of recoverable systems constitutes an excellent method of supporting maintenance related decision-making processes and enables their more rational use.

CORRECTION OF PREDICTION MODEL OUTPUT–APPLICATION TO GENERAL CORROSION MODEL

This paper applies a newly developed methodology to calibrate the corrosion model within a structural reliability analysis. The methodology combines data from experience (measurements and expert judgment) and prediction models to adjust the structural reliability models. Two corrosion models published in the literature have been used to demonstrate the technique used for the model calibration. One model is used as a prediction for a future degradation and a second one to represent the inspection recorded data. The results of the calibration process are presented and discussed.

Portfolio Management of Copula-Dependent Assets Based on P(Y < X) Reliability Models: Revisiting Frank Copula and Dagum Distributions

Modern portfolio theory indicates that portfolio optimization can be carried out based on the mean-variance model, where returns and risk are represented as the average and variance of the historical data of the stock’s returns, respectively. Several studies have been carried out to find better risk proxies, as variance was not that accurate. On the other hand, fewer papers are devoted to better model/characterize returns. In the present paper, we explore the use of the reliability measure P(Y<X) to choose between portfolios with returns given by the distributions X and Y. Thus, instead of comparing the expected values of X and Y, we will explore the metric P(Y<X) as a proxy parameter for return. The dependence between such distributions shall be modelled by copulas. At first, we derive some general results which allows us to split the value of P(Y<X) as the sum of independent and dependent parts, in general, for copula-dependent assets. Then, to further develop our mathematical framework, we chose Frank copula to model the dependency between assets. In the process, we derive a new polynomial representation for Frank copulas. To perform a study case, we considered assets whose returns’ distributions follow Dagum distributions or their transformations. We carried out a parametric analysis, indicating the relative effect of the dependency of return distributions over the reliability index P(Y<X). Finally, we illustrate our methodology by performing a comparison between stock returns, which could be used to build portfolios based on the value of the the reliability index P(Y<X).

Three Cases of Gradual Degradation Mode Analysis of Semiconductor Laser Diodes

Semiconductor laser diodes are important components for various applications such as 5G wireless, datacenter, passive optical network, and aerospace applications. High reliability has emerged to be the universal requirement for all optical applications. To achieve high reliability, fundamental understanding of the laser degradation behavior is crucial. In this paper, we study three cases of gradual degradataion modes of laser diodes including (1) Pattern-A that is associated with threshold current change only, (2) Pattern-B that involve both threshold current and power changes, and (3) Pattern-C that is associated with merely power change. We have instituted reliability equations for the degradation processes. The new reliability models could provide estimation on the laser end-of-life based on the degradation rate and device performance specification.

Construction and Analysis of Queuing and Reliability Models Using Random Graphs

In this paper, the use of the construction of random processes on graphs allows us to expand the models of the theory of queuing and reliability by constructing. These problems are important because the emphasis on the legal component largely determines functioning of these models. The considered models are reliability and queuing. Reliability models arranged according to the modular principle and reliability networks in the form of planar graphs. The queuing models considered here are queuing networks with multi server nodes and failures, changing the parameters of the queuing system in a random environment with absorbing states, and the process of growth of a random network. This is determined by the possibility of using, as traditional probability methods, mathematical logic theorems, geometric images of a queuing network, dual graphs to planar graphs, and a solution to the Dirichlet problem.