Monitoring of Multivariate Time-between-events

Research output: Conference Papers (RGC: 31A, 31B, 32, 33)AbstractNot applicable

View graph of relations

Detail(s)

Original languageEnglish
Publication statusPublished - Jun 2019

Conference

Title11th International Conference on Mathematical Methods in Reliability (MMR2019)
LocationCity University of Hong Kong
PlaceHong Kong
Period3 - 7 June 2019

Abstract

In high-quality processes, a quick way to detect a change in the process is to monitor the time-between-events (TBE). We are interested in the monitoring of multivariate TBE data where we consider multiple processes that are related. Existing multivariate TBE charts are limited in the sense that they only signal after an event occurred for each of the individual processes. This results in slow delayed times (i.e., long time to signal), especially if it is of interest to detect a change in one or a few of the processes. In this talk, we propose a multivariate TBE monitoring method which has the ability to signal after each observed event, i.e. there is no need to wait until an event occurred in each individual process. We derive a mathematical framework for monitoring multivariate TBE data using the distribution function of the superimposed process. We illustrate how the resulting control chart is implemented for the Marshall-Olkin bivariate exponential (MOBE) and Gumbel’s bivariate exponential (GBE) distributions. A simulation study is conducted to compare our method with existing methods.

Bibliographic Note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Citation Format(s)

Monitoring of Multivariate Time-between-events. / MAHMOOD, Tahir; ZWETSLOOT, Inez.

2019. Abstract from 11th International Conference on Mathematical Methods in Reliability (MMR2019), Hong Kong.

Research output: Conference Papers (RGC: 31A, 31B, 32, 33)AbstractNot applicable