eCite Digital Repository
Availability analysis of a LNG processing plant using the Markov process
Citation
Hassan, J and Thodi, P and Khan, FI, Availability analysis of a LNG processing plant using the Markov process, Journal of Quality in Maintenance Engineering, 22, (3) pp. 302-320. ISSN 1355-2511 (2016) [Refereed Article]
Copyright Statement
© Emerald Group Publishing Limited 2016
DOI: doi:10.1108/JQME-05-2012-0018
Abstract
Purpose -
The purpose of this paper is to propose a state dependent stochastic Markov model for availability analysis of process plant instead of traditional time dependent model.
Design/methodology/approach -
The traditional concepts of system performance measurement and reliability (namely, binary; two-state concepts) are observed to be inadequate to characterize performance of complex system components. Availability analysis considering an intermediate state, such as a degraded state, provides a better alternative mechanism for system performance mapping. The availability model provides a better assessment of failure and repair characteristics for equipment in the sub-system and its overall performance. In addition to availability analysis, this paper also discusses the preventive maintenance (PM) program to achieve target availability. In this model, the degraded state is considered as a PM state. Using Markov analysis the optimum maintenance interval is determined.
Findings -
Markov process provides an easier way to measure the performance of the process facility. This study also revealed that the maintenance interval has a major influence in the availability of a process facility as well as in maintaining target availability. The developed model is also applicable to the varying target availability as well as having the capability to handle even the reconfigured process systems.
Research limitations/implications -
,p>Considering the degraded state as an operative state, a higher availability of the plant is predicted. The consideration of the degraded state of the system makes the availability estimation more realistic and acceptable. Availability quantification, target availability allocation and a PM model are exemplified in a sub-system of an liquefied natural gas facility.Originality/value -
The unique features of the present study are; Markov modeling approach integrating availability and PM; optimum PM interval determination of stochastically degrading components based on target availability; consideration of three-state systems; and consideration of increasing failure rates.
Item Details
Item Type: | Refereed Article |
---|---|
Keywords: | Markov process, preventive maintenance,steady-state availability, availability, failure analysis, liquefied natural gas, maintenance, Markov processes, preventive maintenance, stochastic systems, availability analysis, availability estimation |
Research Division: | Mathematical Sciences |
Research Group: | Statistics |
Research Field: | Stochastic Analysis and Modelling |
Objective Division: | Expanding Knowledge |
Objective Group: | Expanding Knowledge |
Objective Field: | Expanding Knowledge in Engineering |
Author: | Khan, FI (Professor Faisal Khan) |
ID Code: | 120367 |
Year Published: | 2016 |
Web of Science® Times Cited: | 2 |
Deposited By: | NC Maritime Engineering and Hydrodynamics |
Deposited On: | 2017-08-23 |
Last Modified: | 2018-04-11 |
Downloads: | 0 |
Repository Staff Only: item control page