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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Main Authors: Rachita Sethi, Amita Bhagat, Deepika Garg
Format: Article
Language:English
Published: International Journal of Mathematical, Engineering and Management Sciences 2019-12-01
Series:International Journal of Mathematical, Engineering and Management Sciences
Subjects:
Online Access:https://www.ijmems.in/assets//120-IJMEMS-19-529-Vol.%204,%20No.%206,%201522%E2%80%931533,%202019.pdf
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spelling 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
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