Erlang Strength Model for Exponential Effects

• Autorzy: Gökhan Gökdere , Mehmet Gürcan
• Języki publikacji: EN

Abstrakty

EN

All technical systems have been designed to perform their intended tasks in a specific ambient. Some systems can perform their tasks in a variety of distinctive levels. A system that can have a finite number of performance rates is called a multi-state system. Generally multi-state system is consisted of components that they also can be multi-state. The performance rates of components constituting a system can also vary as a result of their deterioration or in consequence of variable environmental conditions. Components failures can lead to the degradation of the entire multi-state system performance. The performance rates of the components can range from perfect functioning up to complete failure. The quality of the system is completely determined by components. In this article, a possible state for the single component system, where component is subject to two stresses, is considered under stress-strength model which makes the component multi-state. The probabilities of component are studied when strength of the component is Erlang random variables and the stresses are independent exponential random variables. Also, the probabilities of component are considered when the stresses are dependent exponential random variables.

Słowa kluczowe

EN

Reliability; Stress-Strength Model; Multi-StateSystem; Erlang Distribution; Exponential Distribution

• Czasopismo: Open Physics
• Rocznik: 2015
• Tom: 13
• Numer: 1

Daty

otrzymano

2015-11-11

zaakceptowano

2015-12-01

online

2015-12-31

Twórcy

autor

Gökhan Gökdere

• Department
  of Statistics, Fırat University, 23119, Elazığ, Turkey

autor

Mehmet Gürcan

• Department
  of Statistics, Fırat University, 23119, Elazığ, Turkey

Bibliografia

• [1] K. E. Ahmed, M. E. Fakry, Z. F. Jaheen. J. Statist. Plann. Infer. 64,297 (1997)
• [2] A. M. Awad, M. K. Gharraf. Commun. Statist. Simul. Computat.15, 189 (1986)
• [3] R. D. Brunelle, K.C. Kapur. IIE Transactions. 31, 1171 (1999)
• [4] S. Chandra, D. B. Owen.Naval Res. Log. Quart. 22, 31 (1975)[Crossref]
• [5] N. Ebrahimi. Naval Res. Log. Quart. 31, 671 (1984)[Crossref]
• [6] E. El-Neweihi, F. Proschan, J. Sethuraman. J.Appl. Probab. 15,675 (1978)[Crossref]
• [7] S. Eryılmaz, J. Multivariate Anal. 99, 1878. (2008)[Crossref]
• [8] S. Eryılmaz. IEEE Trans. Reliab. 59, 644, (2010)
• [9] S. Eryılmaz, F. İşçioğlu. Commun. Statist. Theor. Meth. 40, 547(2011)
• [10] A. İ. Genç. J. Statist. Comput. Simul. 83, 326 (2013)
• [11] I. S. Gradshteyn, I. M. Ryzhik. Table of Integrals, Series andProducts, 6th ed.(Academic Press, California, 2000)
• [12] J. C. Hudson, K. C. Kapur. IIE Transactions. 15, 127 (1983)[Crossref]
• [13] S. Kotz, Y. Lumelskii, M. Pensky. The Stress-Strength Model andits Generalizations. Theory and Applications. (Singapore: WorldScientific, 2003)
• [14] W. Kuo, M. J. Zuo. Optimal Reliability Modeling, Principles andApplications. (New York: John Wiley & Sons, 2003)
• [15] A. W. Marshall, I. Olkin. J. Amer. Statist. Soc. 62, 30 (1966)
• [16] N. A. Mokhlis. Commun. Statist. Theor. Meth, 34, 1643 (2005)
• [17] S. Nadarajah, S. Kotz. Mathematical Problems in Engineering.2006, 1 (2006)
• [18] J. G. Surles, W. J. Padgett. J. Appl. Statist. Sci. 7, 225 (2001)
• [19] M. J. Zuo, Z. Tian, H. Z. Huang. IIE Transactions. 39, 811 (2007)[Crossref]

Identyfikatory

DOI

10.1515/phys-2015-0057