Full-text resources of CEJSH and other databases are now available in the new Library of Science.
Visit https://bibliotekanauki.pl

PL EN


2013 | 4 | 1 | 65-75

Article title

A Simple Discrete Approximation for the Renewal Function

Title variants

Languages of publication

EN

Abstracts

EN
Background: The renewal function is widely useful in the areas of reliability, maintenance and spare component inventory planning. Its calculation relies on the type of the probability density function of component failure times which can be, regarding the region of the component lifetime, modelled either by the exponential or by one of the peak-shaped density functions. For most peak-shaped distribution families the closed form of the renewal function is not available. Many approximate solutions can be found in the literature, but calculations are often tedious. Simple formulas are usually obtained for a limited range of functions only. Objectives: We propose a new approach for evaluation of the renewal function by the use of a simple discrete approximation method, applicable to any probability density function. Methods/Approach: The approximation is based on the well known renewal equation. Results: The usefulness is proved through some numerical results using the normal, lognormal, Weibull and gamma density functions. The accuracy is analysed using the normal density function. Conclusions: The approximation proposed enables simple and fairly accurate calculation of the renewal function irrespective of the type of the probability density function. It is especially applicable to the peak-shaped density functions when the analytical solution hardly ever exists.

Publisher

Year

Volume

4

Issue

1

Pages

65-75

Physical description

Dates

published
2013-03-01
online
2013-05-14

Contributors

  • University of Maribor, Faculty of Organizational Sciences, Kranj, Slovenia

References

  • 1. Ayhan H., Limon-Robles, J., Wortman M. A. (1999), „An approach for computing tight numerical bounds on renewal functions”, IEEE Transactions on Reliability, Vol. 48 No. 2, pp. 182-188.
  • 2. Barlow, R. E., Proschan, F., Hunter, L. C. (1996). Mathematical Theory of Reliability, Philadelphia, SIAM.
  • 3. Barouch, E., Kaufman, G. M. (1976), „On Sums of Lognormal Random Variables”. Working paper, Alfred P. Sloan School of Management, Cambridge, Massachusetts, available at http://dspace.mit.edu/bitstream/handle/1721.1/48703/onsumsoflognorma00baro.pdf / (10 June 2011).
  • 4. Bebbington, M., Davydov, Y., Zitikis, R. (2007), „Estimating the renewal function when the second moment is infinite”, Stochastic Models, Vol. 23 No.1, pp. 27 - 48.
  • 5. Beichelt, F. (2006). Stochastic Processes in Science, Engineering And Finance, Boca Raton, Chapman & Hall/CRC.
  • 6. Brezavšček, A. (2011), „Simple Stochastic Model for Planning the Inventory of Spare Components Subject to Wear-out”, Organizacija, Vol. 44 No. 4, pp. 120 - 127.
  • 7. Chaudhry, M. L. (1995), „On computations of the mean and variance of the number of renewals: a unified approach”, The Journal of the Operational Research Society, Vol. 46 No. 11, pp. 1352-1364.
  • 8. Cox, D. R. (1970). Renewal Theory, London & Colchester: Methuen.
  • 9. Cui, L., Xie, M. (2003), „Some normal approximations for renewal function of large Weibull shape parameter”, Communications in Statistics - Simulation and Computation, Vol. 32 No. 1, pp. 1-16.
  • 10. Garg, A., Kalagnanam, J. R. (1998), „Approximations for the renewal function”, IEEE Transactions on Reliability, Vol. 47 No. 1, pp. 66-72.
  • 11. Gertsbakh, I. (2000). Reliability Theory, With Applications to Preventive Maintenance, Berlin: Springer Verglag.
  • 12. Hu, X. (2006), „Approximation of partial distribution in renewal function calculation”, Computational Statistics & Data Analysis, Vol. 50 No. 6, pp. 1615-1624.
  • 13. Jardine, A. K. S. (1973). Maintenance, Replacement, and Reliability, London, Pitman.
  • 14. Jardine, A. K. S., Tsang, A. H. C. (2006). Maintenance, Replacement, and Reliability: Theory and Applications, Boca Raton, CRC/Taylor & Francis.
  • 15. Jiang, R. (2008), „A Gamma-normal series truncation approximation for computing the Weibull renewal function”, Reliability Engineering & System Safety, Vol. 93 No. 4, pp. 616- 626.
  • 16. Jiang, R. (2010), „A simple approximation for the renewal function with an increasing failure rate”, Reliability Engineering & System Safety, Vol. 95 No. 9, pp. 963-969.
  • 17. Johnson, N. L, Kotz, S., Balakrishnan, N. (1994), Continuous Univariate Distributions, Volumes I and II, 2nd. Ed., New York: John Wiley and Sons.
  • 18. Kottegoda, N. T., Rosso, R. (1997). Statistics, Probability, and Reliability for Civil and Environmental Engineers, New York: McGraw-Hill.
  • 19. Lam, C. L. J., Le-Ngoc, T. (2006), „Estimation of typical sum of lognormal random variables using log shifted gamma approximation”, IEEE Communications Letters, Vol. 10 No. 4, pp. 234- 235. [Crossref]
  • 20. Nakagawa, T. (2011). Stochastic Processes: with Applications to Reliability Theory, London: Springer-Verlag.
  • 21. O'Connor, A. N. (2011). Probability Distributions Used in Reliability Engineering, Maryland: RIAC.
  • 22. Politis, K., Koutras, M. V. (2006), „Some new bounds for the renewal function”, Probability in the Engineering and Informational Sciences, Vol. 20 No. 2, pp. 231 - 250.
  • 23. Rinne, H. (2009). The Weibull Distribution: A Handbook, New York: CRC Press, Taylor & Francis Group.
  • 24. Robinson, N. I. (1997), „Renewal functions as series”, Stochastic Models, Vol. 13 No. 3, pp. 577- 604.
  • 25. Romeo, M., Da Costa, V., Bardou, F. (2003), „Broad distribution effects in sums of lognormal random variables”, The European Physical Journal B - Condensed Matter and Complex Systems, Vol. 32 No. 4, pp. 513-525.
  • 26. Sheikh, A. K., Younas, M. (1985), “Renewal Models in Reliability Engineering”, in Deopker, P. E. (Ed.), Failure and Prevention and Reliability, ASME, pp. 93-103.
  • 27. Smeitink, E., Dekker, R. (1990), „A simple approximation to the renewal function”, IEEE Transactions on Reliability, Vol. 39 No. 1, pp. 71-75.
  • 28. Tijms, H. C. (2003). A First Course in Stochastic Models, Chichester: John Wiley & Sons.
  • 29. van Noortwijk, J. M., van der Weide, J. A. M. (2008), „Applications to continuous-time processes of computational techniques for discrete-time renewal processes”, Reliability Engineering & System Safety, Vol. 93 No. 12, pp. 1853-1860.

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.doi-10_2478_bsrj-2013-0006
JavaScript is turned off in your web browser. Turn it on to take full advantage of this site, then refresh the page.