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Vacation model for Markov machine repair problem with two heterogeneous unreliable servers and threshold recovery

机译:具有两个异构的不可靠服务器和阈值恢复的马尔可夫机器维修问题的休假模型

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摘要

Markov model of multi-component machining system comprising two unreliable heterogeneous servers and mixed type of standby support has been studied. The repair job of broken down machines is done on the basis of bi-level threshold policy for the activation of the servers. The server returns back to render repair job when the pre-specified workload of failed machines is build up. The first (second) repairman turns on only when the work load of N~(1)(N~(2)) failed machines is accumulated in the system. The both servers may go for vacation in case when all the machines are in good condition and there are no pending repair jobs for the repairmen. Runge–Kutta method is implemented to solve the set of governing equations used to formulate the Markov model. Various system metrics including the mean queue length, machine availability, throughput, etc., are derived to determine the performance of the machining system. To provide the computational tractability of the present investigation, a numerical illustration is provided. A cost function is also constructed to determine the optimal repair rate of the server by minimizing the expected cost incurred?on the system. The hybrid soft computing method is considered to develop the adaptive neuro-fuzzy inference system (ANFIS). The validation of the numerical results obtained by Runge–Kutta approach is also facilitated by computational results generated by ANFIS.
机译:研究了由两个不可靠的异构服务器和混合型备用支架组成的多部件加工系统的马尔可夫模型。发生故障的机器的维修工作是基于用于激活服务器的二级阈值策略完成的。当故障机器的预定工作量累积时,服务器将返回渲染修复作业。仅当系统中累积了N〜(1)(N〜(2))台故障机器的工作负荷时,第一(第二)修理工才会打开。如果所有机器都处于良好状态,并且维修人员没有待处理的维修工作,则两台服务器都可以休假。 Runge-Kutta方法用于解决用于建立马尔可夫模型的控制方程组。得出各种系统指标,包括平均队列长度,机器可用性,吞吐量等,以确定加工系统的性能。为了提供本研究的计算可处理性,提供了数字说明。还构建了成本函数,以通过最小化系统上的预期成本来确定服务器的最佳维修率。考虑使用混合软计算方法来开发自适应神经模糊推理系统(ANFIS)。 ANFIS生成的计算结果也有助于通过Runge–Kutta方法获得的数值结果的验证。

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