PERFORMANCE MODELING AND ANALYSIS OF A COMPLEX REPAIRABLE INDUSTRIAL SYSTEM

Authors

DOI:

https://doi.org/10.23055/ijietap.2022.29.1.6955

Keywords:

Markov approach, probabilistic approach, transition diagram, Chapman–Kolmogorov equations, corrective maintenance

Abstract

High reliability and availability are the supreme importance of a complex electromechanical system. The imprecise, uncertain, and often inaccurate data collection, uncertainty, and ambiguity have been inevitably associated with a complex industrial system. The Markov approach has proven to be a unified tool to evaluate the reliability of a complex industrial system. In the present research, the author presented a structured and methodological technique to analyze the reliability and availability of various subsystems of coal crushing unit of a thermal power plant using the traditional Markov birth-death process and demonstrated it using a probabilistic approach. The approach consists of breaking up the coal crushing unit/system into various subsystems with three feasible states labeled in the transition diagram. Then using the Markov approach, a probabilistic stochastic model has been developed using Chapman–Kolmogorov equations. The results of the studies are of utmost importance for the plant management in order to take timely decisions for maintaining the system in the upstate for a long duration and take corrective maintenance action.

Author Biography

Sorabh Gupta, Geeta Group of Institutions, Geeta Engineering College, Kurukshetra University, Kurukshetra-Haryana (India)

Professor cum Director, Geeta Group of Institutions, Geeta Engineering College, Panipat (132 001) -Haryana (India)
E mail: drsorabh76@gmail.com; Ph. +91-9996021544

Published

2022-02-25

How to Cite

Gupta, S. (2022). PERFORMANCE MODELING AND ANALYSIS OF A COMPLEX REPAIRABLE INDUSTRIAL SYSTEM. International Journal of Industrial Engineering: Theory, Applications and Practice, 29(1). https://doi.org/10.23055/ijietap.2022.29.1.6955

Issue

Section

Quality, Reliability, Maintenance Engineering