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Presents the analysis of a two‐unit cold standby system in which the standby unit takes a random amount of time for operation whenever the operative unit fails. Each unit is first repaired by the assistant repairman and is then taken up for post‐repair if necessary. The failure and repair times of each unit are assumed to be correlated and their joint density is taken as bivariate exponential. Uses regenerative point technique to obtain various reliability characteristics of interest. Studies the behaviour of steady‐state availability through graphs. Verifies earlier results.

Investigates a stochastic model of a two identical unit cold standby system. Assumes that, if repair of the failed unit is not completed within a specified time, then an order is placed to replace the failed unit by the new one. The specified time is also known as the maximum repair time limit which may change from user to user of the system, so that it is assumed as a random variable. Joint distribution of failure and repair times is bivariate exponential whereas the distributions of lead time (difference between order and delivery time for a new unit) and replacement time of the new unit are negative exponential. Obtains various reliability characteristics of the system under study by using regenerative point technique. Also studied characteristics through graphs.

Profit analysis of a two non‐identical unit cold standby system model with mutual changeover of the units is carried out in this paper. With mutual changeover of the unit, the operating unit, after functioning for some random amount of time, becomes standby to take rest, and the standby unit becomes operative. The failure and repair times of each unit are jointly distributed as bivariate exponential (BVE) with different parameters. Various measures of system effectiveness useful to system engineers and designers are obtained by using the regenerative point technique. Behaviour of the mean time to system failure (MTSF) and availability have also been studied graphically.

This study deals with the reliability analysis of a hybrid series–parallel system consisting of two subsystems A and B with two human operators. Subsystem A has two units in active parallel while subsystem B consists of two-out-of-four units. Both units have exponential failure and repair time. The system under consideration has two states: partial failure state and complete failure state. The mathematical equations associated with the transition diagram have been formulated using regenerative point techniques. The system is analysed using Laplace transforms to solve the mathematical equations. Some important measures of reliability such as availability of system, reliability of the system, mean time to failure (MTTF), sensitivity for MTTF and cost analysis have been discussed. Some particular cases have also been derived and examined to see the practical effect of the model. The computed results are demonstrated by tables and graphs. Furthermore, the results of the designed model are beneficial for system engineers and designers, reliability and maintenance managers.

This paper considered a hybrid series–parallel system consisting of two subsystems A and B with two human operators. The performance of the system is studied using the supplementary variable technique and Laplace transforms. The various measures of reliability such as availability, reliability, mean time to system failure (MTSF), sensitivity for MTTF and cost analysis have been computed for various values of failure and repair rates. Maple 13 software has been used for computations.

In this research paper, the authors have computed various measures of reliability such as availability, reliability, MTSF, sensitivity for MTTF and cost analysis for various values of failure and repair rates and find that failure due to human operators are more responsible for successful operation of the system and also regular repair should be invoked to improve system performance.

This research paper is the original work of authors. The references are well cited based on the importance of study. Nothing has been detached from any research paper or books.

Studies the cost‐benefit analysis of a complex system consisting of two subsystems for example, A and B, connected in series. Subsystem A is composed of two identical units while subsystem B has only one unit. The system functions if one of the two units of subsystem A and the subsystem B are operative. Assuming a bivariate exponential density for the joint distribution of failure and repair times of the units, obtains various reliability characteristics useful to system managers. Also draws explicit results for the case when failure and repair times are independent.

The purpose of this paper is to present age-based replacement models subject to shocks and failure rate in order to determine the optimal replacement cycle. As a result, according to system reliability, maintenance costs of the system are to be minimized.

First, the modeling with respect to assumptions and two major factors (shocks and failure rate) is done. Second, by using of MATLAB the optimal parameters are obtained. Finally, analysis of results and comparison of models are done.

Analysis of results shows all models provide optimal replacement cycle and at this time, cost rate of the system by considering the reliability rate is minimal. Also with an increase of one unit to two units, reliability rate increases much higher than the rate of cost.

This work provides models that in addition to considering the failure rate (internal factors), also shocks as an external factor have been considered. By considering these two factors more comprehensive and adaptable models have been proposed.

The purpose of this paper is to study the combined effect of human error, common‐cause failure, redundancy, and maintenance policies on the performance of a system composed of three‐state devices.

Generalized expressions for time‐dependent and steady state availability of a generalized maintainable three‐state device parallel system subjected to human errors and common‐cause failures are developed in the paper under two maintenance policies: Type I repair policy (i.e. only the completely failed system is repaired); and Type II repair policy (i.e. both partially and completely failed system is repaired). The Markov method is used to develop general and special case expressions for state probabilities, and system time‐dependent and steady state availabilities.

In the case of three‐state devices, it is demonstrated that by increasing the number of redundant devices in parallel do not necessarily lead to the improvement in the system availability. In fact, the availability of the system depends significantly on the dominant failure mode of the devices (i.e. short‐mode or open‐mode). When comparing the effect of maintenance policies on the system availability, it is observed that the Type II repair policy does not lead to an improvement in the system availability. Furthermore, it is observed that both human error and common‐cause failure independently lead to lower system availability.

This study will help maintenance engineers and reliability practitioners to become aware of the combined impact of redundancy, human error, common‐cause failure, and maintenance policies on the performance of the three‐state device systems. Consequently, they will make better maintenance related decisions in organizations such as oil refineries and power stations that use three state devices quite extensively.

Most of the past models have independently studied the effects of redundancy, human error, and common‐cause failure on maintainable system made up of three‐state devices. This effort is one of the first attempts to study the combined effects of all these factors in a parallel system composed of three state devices.

TO SERVE THE INCREASING DEMANDS of their more than 1⅓ million consumers in 223 New Jersey communities, the Public Service Electric and Gas Company, of Newark, N.J., U.S.A., has recently installed the first two units, each of 225,000 kW, at its new $100,000,000 Linden Generating Station which was formally opened in April 1958.

The operating costs and production losses due to equipment failure of offshore gas and oil production systems can exceed initial investment cost. The article explores the probability distribution of downtime associated with random equipment failure and applies availability assessment to design optimisation.

The main objective of this paper is to study the optimal system for series systems with mixed standby (including cold standby, warm standby and hot standby) components.

The paper deals with the reliability and availability characteristics of four different series system configurations. The failure time of the operative, hot standby and warm standby are assumed to be exponentially distributed with parameters λ, λ, and α respectively. The repair time distribution of each server is also exponentially distributed with parameter μ.

The mean time to failure, MTTF_i, and the steady‐state availability A_i(∞) for four configurations are examined and comparisons made. For all four configurations, the configurations are ranked based on: MTTF_i, A_i(∞), and C_i/B_i where B_i is either MTTF_i or A_i(∞). Obviously, the system with height MTTF_i and A_i(∞), do not need frequent maintenance, i.e. less maintenance.

Numerical results for the cost/benefit measure have been obtained for all configurations. It is interesting to note first that the optimal configuration using the cost/MTTF_i measure is configuration 4. Next the optimal configuration using the cost/A_i(∞) measure is configuration 2.