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One of the common approaches to improve systems reliability is using standby redundancy. Although many works are available in the literature on the applications of standby redundancy, the system components are assumed to be independent of each other. But, in reality, the system components can be dependent on one another, causing the failure of each component to affect the failure rate of the remaining active components. In this paper, a standby two-unit system is considered, assuming a dependency between the switch and its associated active component.

This paper assumes that the failures between the switch and its associated active component follow the Marshall–Olkin exponential bivariate exponential distribution. Then, the reliability analysis of the system is done using the continuous-time Markov chain method.

The derived equations application to determine the system steady-state availability, system reliability and sensitivity analysis on the mean time to failure is demonstrated using a numerical illustration.

All previous models assumed independency between the switch and the associated active unit in the standby redundancy approach. In this paper, the switch and its associated component are assumed to be dependent on each other.

The purpose of this paper is to propose a new algorithm for in‐mission trajectories and speed adjustment of multiple unmanned aerial vehicles (UAVs) participating in a mission that requires them to arrive at target location simultaneously with switching and imperfect communication among the vehicles.

This algorithm, programmed at each UAV level, is based on the repeated consensus seeking among the participating vehicles about the time‐on‐target (ToT) through an imperfect inter‐vehicle communication link. The vehicles exchange their individual ToT values repeatedly for a particular duration to pick the highest value among all the vehicles in communication. A consensus confidence flag is set high when consensus is successful. After every consensus cycle with high confidence value, the mission adjustment is carried out by computing difference value between ToT consensus and a threshold value. For the difference values higher than a certain limit, vehicle's trajectory is adjusted by in‐mission insertion of new waypoint (WP) and for lower values the vehicle's speed is varied under allowable limits. The consensus seeking followed by the mission adjustment is repeated periodically to quash the imperfect communication effects.

A mathematical analysis has been carried out to establish the conditions for convergence of the algorithm. The simultaneous arrival of the vehicles subjected to switching communication is achieved only when the union of the switching links during the consensus period enables a vehicle to receive information from all the other vehicles and the switching rate is sufficiently high. This algorithm has been tested in a 6‐degree‐of‐freedom (DoF) multiple UAV simulation environment and achieves simultaneous arrival of multiple fixed wing UAVs under imperfect communication links that meets the aforementioned conditions.

The presented algorithm and design strategy can be extended for other types of cooperative control missions where certain variable of interest is shared among all the vehicles over imperfect communication environment. The design is modular in functionality and can be incorporated into existing vehicles or simulations.

This research presents a new consensus algorithm that repeatedly performs polling of ToT among the vehicles through intermittent communication. The continual nature of consensus seeking covers the weakness of the imperfect communication. A two‐level mission adjustment provides better accuracy in simultaneous arrival at the target location.

In this paper, a new general system consisted of l subsystems connected in series is introduced. Each subsystem connected in K-out-of-(n + m): G mixed standby configuration.

The lifetime of the system's units is assumed to be exponentially distributed and there is elapsed repair time with general distribution. The switch in each subsystem is assumed to be imperfect with the failure process follows an exponential distribution. A genetic algorithm is applied to the system to obtain the optimal solution of the system and solve the redundancy allocation problem.

Analysis of availability, reliability, mean time to failure and steady-state availability of the system is introduced. The measures of the system are discussed in special two cases when the elapsed repair time follows gamma and exponential distribution. An optimization problem with bi-objective functions is introduced to minimize the cost of the system and maximize the reliability function. A numeric application is introduced to show the implementation and effectiveness of the system and redundancy allocation problem.

A new general K-out-of-(n + m): G mixed standby model with elapsed repair time and imperfect switching is introduced.

The internet of things and just-in-time are the embryonic model of innovation for the state-of-the-art design of the service system. This paper aims to develop a fault-tolerant machining system with active and standby redundancy. The availability of the fault-tolerant redundant repairable system is a key concern in the successful deployment of the service system.

In this paper, the authors cogitate a fault-tolerant redundant repairable system of finite working units along with warm standby unit provisioning. Working unit and standby unit are susceptible to random failures, which interrupt the quality-of-service. The system is also prone to common cause failure, which tends its catastrophe. The instantaneous repair of failed unit guarantees the increase in the availability of the unit/system. The time-to-repair by the single service facility for the failed unit follows the arbitrary distribution. For increasing the practicability of the studied model, the authors have also incorporated real-time machining practices such as imperfect coverage of the failure of units, switching failure of standby unit, common cause failure, reboot delay, switch over delay, etc.

For deriving the explicit expression for steady-state probabilities of the system, the authors use a supplementary variable technique for which the only required input is the Laplace–Stieltjes transform (LST) of the repair time distribution.

For complex and multi-parameters distribution of repair time, derivation of performance measures is not possible. The authors prefer numerical simulation because of its importance in the application for real-time uses.

The stepwise recursive procedure, illustrative examples, and numerical results have been presented for the diverse category of repair time distribution: exponential (M), n-stage Erlang (Ern), deterministic (D), uniform (U(a,b)), n-stage generalized Erlang (GE_[n]) and hyperexponential (HE_[n]).

Concluding remarks and future scopes have also been included. The studied fault-tolerant redundant repairable system is suitable for reliability analysis of a computer system, communication system, manufacturing system, software reliability, service system, etc.

As per the survey in literature, no previous published paper is presented with so wide range of repair time distribution in the machine repair problem. This paper is valuable for system design for reliability analysis of the fault-tolerant redundant repairable.

The purpose of this paper is to evaluate various reliability measures like availability, reliability, mean time to failure and profit function.

The authors present a novel method for availability analysis of an engineering system incorporating waiting time to repair. The considered system consists of two subsystems, namely, A and B connected in series. The subsystem B has two identical units in standby arrangement. Each unit of the subsystem has two modes, i.e. normal efficiency or failed. The two standby units of the subsystem B are connected by an imperfect switching. The system is analyzed by supplementary variable technique, Laplace transformation and Gumbel-Hougaard family of copula.

Numerical examples with a way to highlight the important results have been appended at last. Numerical calculation shows that availability and reliability of the system is decreasing with respect to time when failure rates are fixed at different values. Finally, cost analysis of system reveals that the expected profit decreases with increase in service cost.

This paper presents a mathematical model in which an important aspect of switching has been taken into consideration, which is consistent with actual failures of switching by assuming two different types of failure between adjacent transition. It is evaluated with the help of the Gumbel-Hougaard family of copula.

The aim of this study is to demonstrate that hybrid redundancy systems are superior to the conventional N‐modular redundancy (NMR) systems.

The hybrid redundancy system is a synthesis of the NMR system and the standby redundancy. Each module of the NMR has access to k cold spares (k<N) and a repair facility. A semi‐Markov model for the hybrid redundancy system is developed and transient analysis is performed.

Some dependability measures such as availability, reliability, mean time to failure and steady‐state availability are obtained.

This paper presents the transient analysis of the hybrid redundancy systems. The results obtained will be useful to reliability engineers and reliability practitioners.

The purpose of this paper is to present a sensitivity analysis of fault-tolerant redundant repairable computing systems with imperfect coverage, reboot and recovery process.

In this investigation, the authors consider the computing system having a finite number of identical working units functioning simultaneously with the provision of standby units. Working and standby units are prone to random failure in nature and are administered by unreliable software, which is also likely to unpredictable failure. The redundant repairable computing system is modeled as a Markovian machine interference problem with exponentially distributed failure rates and service rates. To excerpt the failed unit from the computing system, the system either opts randomized reboot process or leads to recovery delay.

Transient-state probabilities have been determined with which the authors develop various reliability measures, namely reliability/availability, mean time to failure, failure frequency, and so on, and queueing characteristics, namely expected number of failed units, the throughput of the system and so on, for the predictive purpose. To spectacle the practicability of the developed model, a numerical simulation, sensitivity analysis and so on for different parameters have also been done, and the results are summarized in the tables and graphs. The transient results are helpful to analyze the developing model of the system before having the stability of the system. The derived measures give direct insights into parametric decision-making.

The conclusion has been drawn, and future scope is remarked. The present research study would help system analyst and system designer to make a better choice/decision in order to have the economical design and strategy based on the desired mean time to failure, reliability/availability of the systems and other queueing characteristics.

Different from previous investigations, this studied model provides a more accurate assessment of the computing system compared to uncertain environments based on sensitivity analysis.

The purpose of this paper is to explore the reliability and sensitivity analysis of a system with M primary units, W standby units, and one repair facility when switching to primary units may fail.

Failure times of primary and standby units are assumed to have exponential distributions, and repair times of the failed units are also assumed to have an exponential distribution. Different failure rates and switching failure probabilities are given depending on the readiness states of standby units, designated hot, warm, or cold. The Laplace transform technique is used to transform a set of ordinary differential equations to a set of equations. After finding the solution, we can obtain the desired measures in the time domain by using the inverse Laplace transform.

Expressions for system reliability and mean time to failure (MTTF) are derived. Sensitivity analysis of the system reliability and the MTTF with respect to system parameters are investigated.

This paper presents the first time that a contour of the MTTF with respect to standby states has been obtained, which is quite useful for the decision makers.

The purpose of this paper is to describe the application of low‐glitch current cell in a digital to analog converter (DAC) to reduce the clock‐feedthrough effect and achieve a low power consumption.

A low‐glitch current switch cell is applied in a ten‐bit two‐stage DAC which is composed of a unary cell matrix for six most significant bits and a binary weighted array for four least significant bits (LSBs). The current cell is composed of four transistors to neutralize the clock‐feedthrough effect and it enables DAC to operate in good linearity and low power consumption. The prototype DAC is being implemented in a 0.35μm complementary metal‐oxide semiconductor process. The reduction in glitch energy and power consumption has been realized by preliminary experiment and simulation.

Compared to conventional current cell, more than 15 per cent reduction of glitch energy has been obtained in this work. The DAC is estimated that differential nonlinearity is within 0.1 LSB and the maximum power consumption is 68 mW at the sampling frequency of 100 MHz.

Comparison with other conventional work indicates that the current cell proposed in this paper shows much better performance in terms of switching spike and glitch, which may come from the extra dummy transistor in cell and reduce the clock‐feedthrough effect.

The purpose of this paper is to examine the cost/benefit (C/B) analysis of four configurations for a repairable system with two primary components/units and one standby.

The four configurations are set to the status of the detection and switching failure of standby, as well as the possible reboot of failed units. The time to failure for each of the primary and standby is assumed to follow an exponential distribution. The time to repair and the time to reboot is assumed to have a k‐stage Erlang distribution. The paper develops the explicit expressions of the mean time to failure (or MTTF) and the steady‐state availability (or A) for four various configurations and performed some comparative analysis. Based on the C/B criterion, comparisons are made for specific values of distribution parameters and of the costs of the units. The four various configurations for a repairable system are ranked by using MTTF, A and C/B, where B is either MTTF or A.

Although it is uncertain which configuration is the optimal one among the four ones, the paper provides much comparative information to manager and manufacturers. Managers can use these results to choose the best configuration according to the used data of parameters and selections of the weight of MTTF or Cost/MTTF.

This paper shows a comparative analysis for a two‐unit online repairable system with one standby under four different configurations. It is the first discussion of comparable work on reliability and availability models for redundant repairable systems in which the units are characterized by detection, switching failure and reboot.