The Interval Estimation of MTBF Based on Markov Chain Monte Carlo Method

Yi Dai () and Bin-quan Li ()
Additional contact information
Yi Dai: Tianjin University of Technology and Education
Bin-quan Li: Tianjin University of Technology and Education

Chapter Chapter 65 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 599-607 from Springer

Abstract: Abstract The distribution of time between failures of numerical control (NC) system follows the Weibull distribution, thus it’s estimation of Mean Time Between Failures (MTBF) in reliability engineering is of significance. But there are great difficulties in interval estimation of MTBF using traditional method for Weibull distribution. After the introduction of the approximate estimation, the Markov chain Monte Carlo (MCMC) method is proposed. Combined with the specific characteristics of two-parameter Weibull distribution, Markov chain is established to calculate the interval estimation of MTBF, which solves the problems effectively. And MCMC is more accurate than that of engineering approximation. By analyzing various results in different conditions of MCMC transition kernel, the paper proves that MCMC is a good method for solving interval estimation of Weibull distribution parameters, which has systematic solution process and good adaptability. It greatly enhanced the robustness, effectiveness and accuracy of the calculation.

Keywords: Markov chain; Monte Carlo; Weibull; Interval estimation; Reliability evaluation (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-38433-2_65

Ordering information: This item can be ordered from
http://www.springer.com/9783642384332

DOI: 10.1007/978-3-642-38433-2_65

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().