Intelligent Maintenance System by Using MARKOV Chain with Monte Carlo Simulation Approaches

Journal Title: IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE) - Year 2018, Vol 15, Issue 1

Abstract

This paper presents Markov chain technique as a tool for forecasting the suitable maintenance of machines that helps managers in organizational decision making. Markov process is a tool to predict that it can be make logical and accurate decisions about various aspects of management in the future. Monte Carlo simulation is manipulated in this paper and a new methodology for determination of the transition probabilities in a Markov Decision Process is done. It also illustrates three suggestions for plant maintenance and determines the best plant as a decision support for manager

Authors and Affiliations

Dr. Elsayed A Elsayed, Dr. Shaik Dawood . A. K. , Abdul Rahaman, Dr. R. Karthikeyan

Keywords

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  • EP ID EP437689
  • DOI 10.9790/1684-1501031824.
  • Views 77
  • Downloads 0

How To Cite

Dr. Elsayed A Elsayed, Dr. Shaik Dawood . A. K. , Abdul Rahaman, Dr. R. Karthikeyan (2018). Intelligent Maintenance System by Using MARKOV Chain with Monte Carlo Simulation Approaches. IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE), 15(1), 18-24. https://europub.co.uk/articles/-A-437689