Reliability modeling of a single-unit system with arbitrary distributions subject to different weather conditions
The main concentration of the present study is on the evaluation of some important reliability measures of a single-unit system considering arbitrary distributions for the random variables associated with failure and repair times, time to change of weather conditions, inspection time and arrival tim...
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Published in | International journal of system assurance engineering and management Vol. 5; no. 3; pp. 313 - 319 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
India
Springer India
01.09.2014
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Subjects | |
Online Access | Get full text |
ISSN | 0975-6809 0976-4348 |
DOI | 10.1007/s13198-013-0168-3 |
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Summary: | The main concentration of the present study is on the evaluation of some important reliability measures of a single-unit system considering arbitrary distributions for the random variables associated with failure and repair times, time to change of weather conditions, inspection time and arrival time of the server. The system operates under two weather conditions-normal and abnormal. The unit fails completely via partial failure. There is a single server who takes some time to arrive at the system. Server inspects the unit at its complete failure to see the feasibility of its repair while repair of the unit at partial failure is done without inspection. The unit works as new after repair at partial failure whereas unit is assumed as degraded after repair at complete failure. Inspection of the degraded unit is also conducted at its failure to examine the feasibility of repair. The degraded unit is replaced by new one if inspection reveals that its repair is not feasible to the system. Some measures of system effectiveness are obtained using semi-Markov and regenerative point technique. Giving particular values to various parameters and costs, the numerical results for mean time to system failure, availability and profit function are obtained considering exponential and Rayleigh distributions for all random variables. |
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ISSN: | 0975-6809 0976-4348 |
DOI: | 10.1007/s13198-013-0168-3 |