<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In the industrial sector, maintenance of production facilities plays an important role to carry out production by increasing the reliability and availability of the production process. Predictive maintenance strategy seems adequate to anticipate the failure and degradation of the state of such equipment. A reliability study is needed to quantify indicators to describe the functioning of any system over time. In this paper, we present the results of a stochastic modeling conducted on the analysis of the availability of motor-pump system, installed in a cooling circuit in an industrial complex. The equipment considered in this study is composed of four subsystems. The proposed model is a dynamic Markovian approach, for the purpose of a comparison with the analytical calculation in terms of the indicators’ evaluation of the dependability of the studied system, including instant availability. The different states of the system components and the transition functions between these states have also been characterized. The results of availability obtained by the model are well correlated with those calculated analytically, confirming that the proposed model is very powerful, it will help predict the future states of the system, in order to predict any necessary preventive maintenance actions.</p></abstract>

In the industrial sector, maintenance of production facilities plays an important role to carry out production by increasing the reliability and availability of the production process. Predictive maintenance strategy seems adequate to anticipate the failure and degradation of the state of such equipment. A reliability study is needed to quantify indicators to describe the functioning of any system over time. In this paper, we present the results of a stochastic modeling conducted on the analysis of the availability of motor-pump system, installed in a cooling circuit in an industrial complex. The equipment considered in this study is composed of four subsystems. The proposed model is a dynamic Markovian approach, for the purpose of a comparison with the analytical calculation in terms of the indicators’ evaluation of the dependability of the studied system, including instant availability. The different states of the system components and the transition functions between these states have also been characterized. The results of availability obtained by the model are well correlated with those calculated analytically, confirming that the proposed model is very powerful, it will help predict the future states of the system, in order to predict any necessary preventive maintenance actions.

Study of Reliability in a Repairable System by Markov Chains

Department of Mechanical Engineering, Faculty of Technology

Department of Mechanical Engineering, Faculty of Technology, LRPCSI Laboratory of research

Acta Universitatis Sapientiae, Electrical and Mechanical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Study of Reliability in a Repairable System by Markov Chains"}

In the industrial sector, maintenance of production facilities plays an important role to carry out production by increasing the reliability and availability...

Study of Reliability in a Repairable System by Markov Chains

Publié en ligne: 31 déc. 2020

Pages: 66 - 76

Reçu: 15 nov. 2019

Accepté: 11 nov. 2020

DOI: https://doi.org/10.2478/auseme-2020-0005

Mots clés
Reliability, repairable system, Markov chain, modelling, transition matrix

© 2020 Naima Tamaloussi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Study of Reliability in a Repairable System by Markov Chains

Publié en ligne: 31 déc. 2020

Pages: 66 - 76

Reçu: 15 nov. 2019

Accepté: 11 nov. 2020

DOI: https://doi.org/10.2478/auseme-2020-0005

Mots clésReliability, repairable system, Markov chain, modelling, transition matrix

© 2020 Naima Tamaloussi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Reliability, repairable system, Markov chain, modelling, transition matrix