ANFIS based Machine Repair Model with Control Policies and Working Vacation
This study is concerned with the transient state analysis of M/M/1 machine repairable system consisting of M operating units. F-policy is quite useful to avoid the overloading of failed machines that arrive for repair in the system. The failed machines are repaired by a server that is susceptible to...
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International Journal of Mathematical, Engineering and Management Sciences
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doaj-e9e22ecbd4da4317843d1cc7552f33872020-11-25T02:15:20ZengInternational Journal of Mathematical, Engineering and Management SciencesInternational Journal of Mathematical, Engineering and Management Sciences2455-77492455-77492019-12-01461522153310.33889/IJMEMS.2019.4.6-120ANFIS based Machine Repair Model with Control Policies and Working VacationRachita Sethi0Amita Bhagat1Deepika Garg2Department of Mathematics, G. D. Goenka University, Gurugram-122103, IndiaDepartment of Mathematics, Jaypee Institute of Information Technology, Noida- 201309, IndiaDepartment of Mathematics, G. D. Goenka University, Gurugram-122103, IndiaThis study is concerned with the transient state analysis of M/M/1 machine repairable system consisting of M operating units. F-policy is quite useful to avoid the overloading of failed machines that arrive for repair in the system. The failed machines are repaired by a server that is susceptible to failure and follows the threshold recovery while being repaired. The server leaves for a vacation if there are no machines waiting in the system for the repair. Runge-Kutta method is implemented to solve the governing equations and evaluate the system's state probabilities. Cost function is also designed to determine the system’s minimum cost. In addition, the numerical outcomes acquired by the Runge-Kutta method are compared with the results generated by adaptive neuro-fuzzy inference system (ANFIS).https://www.ijmems.in/assets//120-IJMEMS-19-529-Vol.%204,%20No.%206,%201522%E2%80%931533,%202019.pdfMachine-repairStart-up timeThreshold recoveryCost analysisANFIS |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rachita Sethi Amita Bhagat Deepika Garg |
spellingShingle |
Rachita Sethi Amita Bhagat Deepika Garg ANFIS based Machine Repair Model with Control Policies and Working Vacation International Journal of Mathematical, Engineering and Management Sciences Machine-repair Start-up time Threshold recovery Cost analysis ANFIS |
author_facet |
Rachita Sethi Amita Bhagat Deepika Garg |
author_sort |
Rachita Sethi |
title |
ANFIS based Machine Repair Model with Control Policies and Working Vacation |
title_short |
ANFIS based Machine Repair Model with Control Policies and Working Vacation |
title_full |
ANFIS based Machine Repair Model with Control Policies and Working Vacation |
title_fullStr |
ANFIS based Machine Repair Model with Control Policies and Working Vacation |
title_full_unstemmed |
ANFIS based Machine Repair Model with Control Policies and Working Vacation |
title_sort |
anfis based machine repair model with control policies and working vacation |
publisher |
International Journal of Mathematical, Engineering and Management Sciences |
series |
International Journal of Mathematical, Engineering and Management Sciences |
issn |
2455-7749 2455-7749 |
publishDate |
2019-12-01 |
description |
This study is concerned with the transient state analysis of M/M/1 machine repairable system consisting of M operating units. F-policy is quite useful to avoid the overloading of failed machines that arrive for repair in the system. The failed machines are repaired by a server that is susceptible to failure and follows the threshold recovery while being repaired. The server leaves for a vacation if there are no machines waiting in the system for the repair. Runge-Kutta method is implemented to solve the governing equations and evaluate the system's state probabilities. Cost function is also designed to determine the system’s minimum cost. In addition, the numerical outcomes acquired by the Runge-Kutta method are compared with the results generated by adaptive neuro-fuzzy inference system (ANFIS). |
topic |
Machine-repair Start-up time Threshold recovery Cost analysis ANFIS |
url |
https://www.ijmems.in/assets//120-IJMEMS-19-529-Vol.%204,%20No.%206,%201522%E2%80%931533,%202019.pdf |
work_keys_str_mv |
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