Multi-Point and Multi-Interval Bounded-Covering Availability Measures for Aggregated Markovian Repairable Systems

He Yi (), Lirong Cui, Narayanaswamy Balakrishnan and Jingyuan Shen
Additional contact information
He Yi: Beijing University of Chemical Technology
Lirong Cui: Qingdao University
Narayanaswamy Balakrishnan: McMaster University
Jingyuan Shen: Nanjing University of Science and Technology

Methodology and Computing in Applied Probability, 2022, vol. 24, issue 4, 2427-2453

Abstract: Abstract In reliability theory, there are many measures for describing the characteristics of repairable systems, such as reliability, point availability and interval availability. However, these reliability measures do not cover some situations that one may be interested in. In this work, two new reliability measures, multi-point bounded-covering availability and multi-interval bounded-covering availability, are introduced, and derived in matrix form for aggregated Markovian repairable systems. The formulas for single-point, single-interval, binary-point and binary-interval bounded-covering availabilities are all obtained by an enumeration method. The formulas for multi-point and multi-interval bounded-covering availabilities are given in a recursive computational form. Some properties of these two new measures are then discussed briefly, and a few numerical examples are provided to illustrate the results presented here. Finally, some conclusions and discussions are given.

Keywords: Reliability measure; Aggregated markovian repairable system; Multi-point; Multi-interval; Bounded-covering availability; 90B25; 60J27; 60K10 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11009-022-09936-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:metcap:v:24:y:2022:i:4:d:10.1007_s11009-022-09936-3

Ordering information: This journal article can be ordered from
https://www.springer.com/journal/11009

DOI: 10.1007/s11009-022-09936-3

Access Statistics for this article

Methodology and Computing in Applied Probability is currently edited by Joseph Glaz

More articles in Methodology and Computing in Applied Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().