Sensitivity analysis of a three-unit series system under k-out-of-n redundancy

Abstract

Purpose The purpose of this paper is to investigate the reliability measures, namely, availability, reliability, mean time to failure and expected profit. The authors also analyse the sensitivity of these reliability measures. Design/methodology/approach Depending upon the real industrial relevance, a generalized system which is easily repairable, extremely reliable and of high quality is expected by the rapid growth of the digital economy. Considering reliability, as one of the performance measure, the authors have designed a complex system which consists of three subsystems, namely, A, B and C in series configuration. The subsystem A consists of n numbers of units which are arranged in parallel configuration, subsystem B consists of two sub-subsystems X and Y align parallel to one another, where X is a type of 1-out-of-n:F. Failure and repair rates are assumed to be follow the general distribution. Findings The system is deeply studied by the usage of the supplementary variable technique, Laplace transformation and Markov’s law. Various conclusive results such as availability and reliability of the system, mean time to failure, cost and sensitivity analysis have been discussed further. Originality/value Through the systematic view of reliability measures of the proposed system, performance of the system can be enhanced under high profit.

Evaluating and Improving a Content Delivery Network (CDN) Workflow using Stochastic Modelling

“…System is how much reliable, can be calculated by taking the inverse Laplace transformation of Equation ( 16) and setting the value of various parameters as l = 0.35, c = 0.3, α = 0.4, r = 0.3, w r = 0.08, φ(x) = 0 [20,21], one can obtain reliability of the system in terms of time t as Rl(t) = 3.571428571e (−0.4 t) + 0.4032258065e (−0.48 t) + 0.04049713727e (−1.1 t) − 3.333333333e (−0.5 t) + 0.3181818182 (18)…”

“…Consider the repair facility is available. Setting the value of various parameters as l = 0.35, c = 0.3, α = 0.4, r = 0.3, w r = 0.08, φ(x) = 1 [20][21][22] and taking the inverse Laplace transformation of Equation ( 16), one can obtain availability of the system in terms of time t as Av(t) = 5.588049614e (−0.48 t) − 0.03125888036e (−1.5 t) + 0.018269368e (−1.972841614 t) − 5.067581468e (−0.5271583855 t) + 0.4925213675 Now varying the time t from 0 to 15 in Equation ( 19), one obtains the availability of designed system as shown in Table 3 and corresponding Figure 4 respectively.…”

System reliability-redundancy allocation by the multiobjective plant propagation algorithm

“…In the process, they try to tackle a number of challenges by optimizing the design of such plants. Reliability-redundancy allocation is one of the efficient methods that allows to increase the overall system reliability (Aksezer, 2016;Goyal et al, 2017;Hsieh et al, 1998;Mellal and Williams, 2018;Zio, 2016, 2017). However, if the reliability is increased, then cost also increases.…”

A closed-form equation for steady-state availability of cold standby repairable k-out-of-n

“…For instance, Kenyon and Newell (1983) calculated the steady-state availability of a k -out-of- n system with repairable components. Goyal et al (2017) obtained the availability and reliability of a three-unit series system with k -out-of- n redundancy alongside its mean time to failure. Zhang et al (2006) analyzed a warm standby k -out-of-( M + N ) system and calculated the steady-state availability for some particular systems using the Markov method and transient state process.…”