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In this paper, reliability measures of two dual-unit systems having non-identical units are compared under different weather conditions namely normal & abnormal in steady state using semi-Markov process and regenerative point technique. In both the models, initially original unit (called as main unit) is operative while the other substandard unit (called as duplicate unit) is kept at cold standby mode. Two units either have normal mode of operation or failed. There is a single server who performs the repair activities of both units in normal weather conditions only. Server leaves the system in abnormal weather conditions. In model I, neither operation nor repair activities are allowed in abnormal weather conditions but in model II, operation of both units are allowed in different weather conditions. The distribution for failure times of the units and time to change of weather conditions are taken as negative exponential while that of repair time of the units are arbitrary. All random variables are statistically independent. The results for some important reliability measures such as MTSF, availability, busy period of server, expected number of visits by the server have been analyzed for arbitrary values of various parameters and costs. Reliability comparisons and profit comparisons are made between the two systems.
Keywords:
Dual-unit system, Semi-Markov process, Regenerative point technique
Cite Article:
"Tabular Comparison of Two similar Dual-unit Systems with single server", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.2, Issue 2, page no.34 - 46, February-2017, Available :http://www.ijrti.org/papers/IJRTI1702008.pdf
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000204873
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator